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Brain modeling has been receiving significant attention over the years, both for its neuroscientific potential and for its challenges in the context of high-performance computing. The development of physiologically plausible neuron models comes at the cost of increased complexity. In this work, we have selected a highly computationally demanding model of the Inferior-Olivary Nucleus (InfOli) based on the Hodgkin-Huxley (HH) neuron model. This brain region, functionally coupled with the cerebellum, is of vital importance for motor skills and time-sensitive cognitive functions. The computing fabric of choice is an Intel Xeon/Xeon Phi system, which is a typical node of modern computing infrastructure. The target application is parallelized with various combinations of MPI and OpenMP and performance is measured on the target platform. The different implementations are compared and the best one is chosen. Further optimization of this implementation is presented in detail. Its behaviour is then examined when scaling up to neuron populations representative of realistic, human Inferior-Olivary neuronal networks. The evaluation’s results highlight the importance of examining a network’s size and density before choosing the best platform for its simulation. All the parallelization and vectorization options presented in the current paper are available on a public repository for further examination. [ABSTRACT FROM AUTHOR]

Editorial. Presents information about articles related to middleware computer network infrastructures, published in the November 2003 issue of the journal "IEEE Transactions on Parallel and Distributed Systems." Highlights of the paper published in this issue of the journal by author Charles Zhang and colleagues, that presents an introduction of aspect-oriented computer programming techniques within object request brokers; Features of the paper authored by P. Ferreira and colleagues, that describes a middleware platform called OBIWAN; Appreciation from the author to all the reviewers who provided useful feedback to select papers for this issue of the journal.

Many data-intensive applications like MapReduce are network-bound in data centers, due to transfer massive amount of flows across successive processing stages. Data flows in such an incast or shuffle transfer are highly correlated and aggregated at the receiver side. Prior work aims to aggregate correlated flows of each transfer, during the transmission phase as early as possible, so as to directly lower down the network traffic. However, many applications do not constrain the flows’ endpoints of each transfer as long as certain constraints are satisfied. Such uncertain transfers bring new opportunities and challenges to lower down the network traffic than prior deterministic transfers. In this paper, we focus on aggregating an uncertain incast transfer and minimizing the amount of caused network traffic. Prior approaches, relying on deterministic incast transfers, remain inapplicable. This paper makes the first step towards the study of aggregating uncertain incast transfer. We propose efficient approaches from two aspects, i.e., the initialization of uncertain senders and the incast tree building. We first design two initialization methods to pick the best deterministic senders for an uncertain incast transfer, so as to form the least number of disjoint sender groups. Thus, flows from each group would be aggregated as one flow on a common one-hop neighbor, irrespective of the location of a picked receiver. Accordingly, we propose the interstage-based and intrastage-based incast tree building methods to exploit the benefits of our initialization methods. We provide evidence to show that our approach can achieve the benefits of in-network aggregation for any uncertain incast transfer. Moreover, an uncertain incast transfer significantly outperforms any related deterministic one, in terms of the reduced network traffic and the saved network resources. [ABSTRACT FROM PUBLISHER]

Abstract-As genome sequence databases grow in size, the accuracy and speed of sequence similarity detection have become more important. Over the last few years, a number of methods have been introduced for detecting sequence similarity. Also, the demands for genome sequence search and alignment services have also increased. It is a tremendous challenge to scale up computer systems so that they can host various methods and service requests to these methods in a timely manner. Traditional clusters, which are used in most scientific centers today, cannot cope with this challenge very well. This paper tackles this problem in a novel way, which treats sequence search requests as content requests to both genome databases and similarity detection methods. Therefore, scaling up the computer systems that serve these contents is a a process of constructing a content distribution network (CDN). This paper proposes a decentralized method to dynamically construct CDNs for a variety of genome sequence similarity detection services. This paper also provides a scheduling algorithm for the efficient use of content nodes. The simulation study shows that scalability arid high content node utilization can be achieved in such a system t a reasonable cost. [ABSTRACT FROM AUTHOR]

Dynamical connection graph changes are inherent in networks such as peer-to-peer networks, wireless ad hoc networks, and wireless sensor networks. Considering the influence of the frequent graph changes is, thus, essential for precisely assessing the performance of applications and algorithms on such networks. In this paper, using stochastic hybrid systems (SHSs), we model the dynamics and analyze the performance of an epidemic-like algorithm, Distributed Random Grouping (DRG), for average aggregate computation on a wireless sensor network with dynamical graph changes. Particularly, we derive the convergence criteria and the upper bounds on the running time of the ORG algorithm for a set of graphs that are individually disconnected but jointly connected in time. An effective technique for the computation of a key parameter in the derived bounds is also developed. Numerical results and an application extended from our analytical results to control the graph sequences are presented to exemplify our analysis. [ABSTRACT FROM AUTHOR]

This paper formulates abstract problems of assigning subtasks to agents (processors) in a distributed system with a goal that they can perform its global task efficiently. The paper models the distributed system with a graph that describes the communication capabilities of the constituting agents. This graph is referred to as the ‘organizational graph.’ In addition, the desired task-performing activity is modeled with another graph describing the required communications. Then, a few variants of the task assignment problem are formulated with potentially conflicting objectives (or constraints) of load balancing and communication costs. For some of these variants this paper provides efficient algorithms that solve the assignment problem. Some problems are proven NP-complete, and some others are left open. [ABSTRACT FROM AUTHOR]

In the late years many different interconnection networks have been used with two main tendencies. One is characterized by the use of high-degree routers with long wires while the other uses routers of much smaller degree. The latter rely on two-dimensional mesh and torus topologies with shorter local links. This paper focuses on doubling the degree of common 2D meshes and tori while still preserving an attractive layout for VLSI design. By adding a set of diagonal links in one direction, diagonal networks are obtained. By adding a second set of links, networks of degree eight are built, named king networks. This research presents a comprehensive study of these networks which includes a topological analysis, the proposal of appropriate routing procedures and an empirical evaluation. King networks exhibit a number of attractive characteristics which translate to reduced execution times of parallel applications. For example, the execution times NPB suite are reduced up to a 30 percent. In addition, this work reveals other properties of king networks such as perfect partitioning that deserves further attention for its convenient exploitation in forthcoming high-performance parallel systems. [ABSTRACT FROM PUBLISHER]

Dragonfly topologies are gathering great interest nowadays as one of the most promising interconnect options for High-Performance Computing (HPC) systems. However, Dragonflies contain physical cycles that may lead to traffic deadlocks unless the routing algorithm prevents them properly. In general, existing deadlock-free routing algorithms, either deterministic or adaptive, proposed for Dragonflies, use Virtual Channels (VCs) to prevent cyclic dependencies. However, these topology-aware algorithms are difficult to implement, or even unfeasible, in systems based on the InfiniBand (IB) architecture, which is nowadays the most widely used network technology in HPC systems. This is due to some limitations in the IB specification, specifically regarding the way Virtual Lanes (VLs), which are considered as similar to VCs, can be assigned to traffic flows. Indeed, none of the routing engines currently available in the official releases of the IB control software has been specifically proposed for Dragonflies. In this paper, we present a new deterministic, minimal-path routing for Dragonfly that prevents deadlocks using VLs according to the IB specification, so that it can be straightforwardly implemented in IB-based networks. We have called this proposal D3R (Deterministic Deadlock-free Dragonfly Routing). Specifically, D3R maps each route to a single, specific VL depending on the destination group, and according to a specific order, so that cyclic dependencies (so deadlocks) are prevented. D3R is scalable as it requires only 2 VLs to prevent deadlocks regardless of network size, i.e., fewer VLs than the required by the deadlock-free routing engines available in IB that are suitable for Dragonflies. Alternatively, D3R achieves higher throughput if an additional VL is used to reduce internal contention in the Dragonfly groups. We have implemented D3R as a new routing engine in OpenSM, the control software including the subnet manager in IB. We have evaluated D3R by means of simulation and by experiments performed in a real IB-based cluster, the results showing that, in general, D3R outperforms other routing engines. [ABSTRACT FROM PUBLISHER]

This paper addresses the data search problem in large-scale highly mobile and dense wireless networks. Current wireless network data search systems are not suitable for large-scale highly mobile and dense wireless networks. This paper presents a scalable and mobility-resilient LOcality-based distRibuted Data search system (LORD) for large-scale wireless networks with high mobility and density. Taking advantage of the high density, rather than mapping data to a location point, LORD maps file metadata to a geographical region and stores it in multiple nodes in the region, thus enhancing mobility-resilience. LORD has a novel region-based geographic data routing protocol that does not rely on flooding or GPSs for data publishing and querying, and a coloring-based partial replication algorithm to reduce data replicas in a region while maintaining the querying efficiency. LORD also works for unbalanced wireless networks with sparse regions. Simulation results show the superior performance of LORD compared to representative data search systems in terms of scalability, overhead, and mobility resilience in a highly dense and mobile network. The results also show the high scalability and mobility-resilience of LORD in an unbalanced wireless network with sparse regions, and the effectiveness of its coloring-based partial replication algorithm. [ABSTRACT FROM AUTHOR]

The ephemeral content popularity seen with many content delivery applications can make indiscriminate on-demand caching in edge networks highly inefficient, since many of the content items that are added to the cache will not be requested again from that network. In this paper, we address the problem of designing and evaluating more selective edge-network caching policies. The need for such policies is demonstrated through an analysis of a dataset recording YouTube video requests from users on an edge network over a 20-month period. We then develop a novel workload modelling approach for such applications and apply it to study the performance of alternative edge caching policies, including indiscriminate caching and cache on $k$ th request for different $k$ . The latter policies are found able to greatly reduce the fraction of the requested items that are inserted into the cache, at the cost of only modest increases in cache miss rate. Finally, we quantify and explore the potential room for improvement from use of other possible predictors of further requests. We find that although room for substantial improvement exists when comparing performance to that of a perfect “oracle” policy, such improvements are unlikely to be achievable in practice. [ABSTRACT FROM AUTHOR]

The increasing number of cores on a chip has made the network on chip (NoC) concept the standard communication paradigm for chip multiprocessors. A fault in an NoC leads to undesirable ramifications that can severely impact the performance of a chip. Therefore, it is vital to design fault tolerant NoCs. In this paper, we present Shield , a reliable NoC router architecture that has the unique ability to tolerate both hard and soft errors in the routing pipeline using techniques such as spatial redundancy, exploitation of idle cycles, bypassing of faulty resources and selective hardening. Using Mean Time to Failure and Silicon Protection Factor metrics, we show that Shield is six times more reliable than the baseline-unprotected router and is at least 1.5 times more reliable than existing fault tolerant router architectures. We introduce a new metric called Soft Error Improvement Factor and show that the soft error tolerance of Shield has improved by three times in comparison to the baseline-unprotected router. This reliability improvement is accomplished by incurring an area and power overhead of 34 and 31 percent respectively. Latency analysis using SPLASH-2 and PARSEC reveals that in the presence of faults, latency increases by a modest 13 and 10 percent respectively. [ABSTRACT FROM AUTHOR]

Virtualization of servers and networks is a key technique to resolve the conflict between the increasing demands on computing power and the high cost of hardware in data centers. In order to map virtual networks to physical infrastructure efficiently, designers have to make careful decisions on the allocation of limited resources, which makes placement of virtual networks in data centers a critical issue. In this paper, we study the placement of virtual networks in fat-tree data center networks. In order to meet the requirements of instant parallel data transfer between multiple computing units, we propose a model of multicast-capable virtual networks (MVNs). We then design four virtual machine (VM) placement schemes to embed MVNs into fat-tree data center networks, named Most-Vacant-Fit (MVF), Most-Compact-First (MCF), Mixed-Bidirectional-Fill (MBF), and Malleable-Shallow-Fill (MSF). All these VM placement schemes guarantee the nonblocking multicast capability of each MVN while simultaneously achieving significant saving in the cost of network hardware. In addition, each VM placement scheme has its unique features. The MVF scheme has zero interference to existing computing tasks in data centers; the MCF scheme leads to the greatest cost saving; the MBF scheme simultaneously possesses the merits of MVF and MCF, and it provides an adjustable parameter allowing cloud providers to achieve preferred balance between the cost and the overhead; the MSF scheme performs at least as well as MBF, and possesses some additional predictable features. Finally, we compare the performance and overhead of these VM placement schemes, and present simulation results to validate the theoretical results. [ABSTRACT FROM AUTHOR]

Many applications in several domains such as telecommunications, network security, large-scale sensor networks, require online processing of continuous data flows. They produce very high loads that requires aggregating the processing capacity of many nodes. Current Stream Processing Engines do not scale with the input load due to single-node bottlenecks. Additionally, they are based on static configurations that lead to either under or overprovisioning. In this paper, we present StreamCloud, a scalable and elastic stream processing engine for processing large data stream volumes. StreamCloud uses a novel parallelization technique that splits queries into subqueries that are allocated to independent sets of nodes in a way that minimizes the distribution overhead. Its elastic protocols exhibit low intrusiveness, enabling effective adjustment of resources to the incoming load. Elasticity is combined with dynamic load balancing to minimize the computational resources used. The paper presents the system design, implementation, and a thorough evaluation of the scalability and elasticity of the fully implemented system. [ABSTRACT FROM PUBLISHER]

In this paper, we address attacks that exploit the timing behavior of TCP and other protocols and applications in low-latency anonymity networks. Mixes have been used in many anonymous communication systems and are supposed to provide countermeasures to defeat traffic analysis attacks. In this paper, we focus on a particular class of traffic analysis attacks, flowcorrelation attacks, by which an adversary attempts to analyze the network traffic and correlate the traffic of a flow over an input link with that over an output link. Two classes of correlation methods are considered, namely time-domain methods and frequency-domain methods. Based on our threat model and known strategies in existing mix networks, we perform extensive experiments to analyze the performance of mixes. We find that all but a few batching strategies fail against flow-correlation attacks, allowing the adversary to either identify ingress and egress points of a flow or to reconstruct the path used by the flow. Counter intuitively, some batching strategies are actually detrimental against attacks. The empirical results provided in this paper give an indication to designers of Mix networks about appropriate configurations and mechanisms to be used to counter flow-correlation attacks. [ABSTRACT FROM AUTHOR]

This paper studies the problem of realizing a common software clock among a large set of nodes without an external time reference (i.e., internal clock synchronization), any centralized control, and where nodes can join and leave the distributed system at their will. The paper proposes an internal clock synchronization algorithm which combines the gossip-based paradigm with a nature-inspired approach, coming from the coupled oscillators phenomenon, to cope with scale and churn. The algorithm works on the top of an overlay network and uses a uniform peer sampling service to fulfill each node's local view. Therefore, differently from clock synchronization protocols for small scale and static distributed systems, here, each node synchronizes regularly with only the neighbors in its local view and not with the whole system. An evaluation of the convergence speed and the synchronization error of the coupled-based internal clock synchronization algorithm has been carried out, showing how convergence time and the synchronization error depends on the coupling factor and the local view size. Moreover, the variation of the synchronization error with respect to churn and the impact of a sudden variation of the number of nodes have been analyzed to show the stability of the algorithm. In all these contexts, the algorithm shows nice performance and very good self-organizing properties. Finally, we showed how the assumption on the existence of a uniform peer-sampling service is instrumental for the good behavior of the algorithm and how, in system models where network delays are unbounded, a mean-based convergence function reaches a lower synchronization error than median-based convergence functions exploiting the number of averaged clock values. [ABSTRACT FROM AUTHOR]

This paper presents the development and implementation of a multiprocessor system-on-chip solution for fast and real-time simulations of complex and nonlinear wheel-rail contact mechanics. There are two main significances in this paper. First, the wheel-rail contact laws (including Hertz and Fastsim algorithms), which are widely used in the study of railway vehicle dynamics, are restructured for improved suitability that can take advantage of the rapid developing multiprocessor technology. Second, the complex algorithms for the contact laws are successfully implemented on a medium-sized Field-Programmable Gate Array (FPGA) device using six NiosII processors, where the executions of the Hertz and Fastsim parts are pipelined to achieve further enhancement in multiple contacts and the operation scheduling is optimized. In the Fastsim part, the floating point units with buffering mechanism are efficiently shared by five processors connected in a token ring topology. The FPGA design shows good flexibility in utilizing logic element and on-chip memory resource on the device and scalability for a significant speed up on a larger device in future work. [ABSTRACT FROM AUTHOR]

Abstract-Data Distribution Management (DDM) is one of the most critical component of any large-scale interactive distributed simulation systems. The aim of DDM is to reduce and control the volume of information exchanged among the simulated entities (federates) in a large-scale distributed simulation system. In order to fulfill its goal, a considerable amount of DDM messages needs to be exchanged within the simulation (federation). The question of whether each message should be sent immediately after it is generated or held until it can be grouped with other DDM messages needs to be investigated further. Our experimental results have shown that the total DDM time of a simulation varies considerably depending on which transmission strategy is used. Moreover, in the case of grouping, the DDM time depends on the size of the group. In this paper, we propose a novel DDM approach, which we refer to as Adaptive Grid-based (AGB) DDM. The AGB protocol is distinct from all existing DDM implementations, because it is able to predict the average amount of data generated in each time step of a simulation. Therefore, the AGB DDM approach controls a simulation running in the most appropriate mode to achieve a desired performance. This new DDM approach consists of two adaptive control parts: 1) the Adaptive Resource Allocation Control (ARAC) scheme and 2) the Adaptive Transmission Control (ATC) scheme. The focus of this paper is on the ATC scheme. We describe how to build a switching model to predict the average amount of DDM messages generated and how the ATC scheme uses this estimation result to optimize the overall DDM time. Our experimental results provide a clear evidence that the ATC scheme is able to achieve the best performance in DDM time when compared to all existing DDM protocols using an extensive set of experimental case studies. [ABSTRACT FROM AUTHOR]

Abstract-Fail-stop failures in distributed environments are often tolerated by checkpointing or message logging. In this paper, we show that fail-stop process failures in ScaLAPACK matrix-matrix multiplication kernel can be tolerated without checkpointing or message logging. It has been proved in the previous algorithm-based fault tolerance research that, for matrix-matrix multiplication, the checksum relationship in the input checksum matrices is preserved at the end of the computation no matter which algorithm is chosen. From this checksum relationship in the final computation results, processor miscalculations can be detected, located, and corrected at the end of the computation. However, whether this checksum relationship in the input checksum matrices can be maintained in the middle of the computation or not remains open. In this paper, we first demonstrate that, for many matrix-matrix multiplication algorithms, the checksum relationship in the input checksum matrices is not maintained in the middle of the computation. We then prove that, however, for the outer product version matrix-matrix multiplication algorithm, the checksum relationship in the input checksum matrices can be maintained in the middle of the computation. Based on this checksum relationship maintained in the middle of the computation, we demonstrate that fail-stop process failures in ScaLAPACK matrix-matrix multiplication can be tolerated without checkpointing or message logging. Because no periodical checkpointing is involved, the fault tolerance overhead for this approach is surprisingly low. [ABSTRACT FROM AUTHOR]

Firewalls are the mainstay of enterprise security and the most widely adopted technology for protecting private networks. An error in a firewall policy either creates security holes that will allow malicious traffic to sneak into a private network or blocks legitimate traffic and disrupts normal business processes, which, in turn, could lead to irreparable, if not tragic, consequences. It has been observed that most firewall policies on the Internet are poorly designed and have many errors. Therefore, how one can design firewall policies correctly is an important issue. In this paper, we propose the method of diverse firewall design, which consists of three phases: a design phase, a comparison phase, and a resolution phase. In the design phase, the same requirement specification of a firewall policy is given to multiple teams who proceed independently to design different versions of the firewall policy. In the comparison phase, the resulting multiple versions are compared with each other to detect all functional discrepancies between them. In the resolution phase, all discrepancies are resolved, and a firewall that is agreed upon by all teams is generated. The major technical challenge in the method of diverse firewall design is how one can discover all functional discrepancies between two given firewall policies. We present a series of three efficient algorithms for solving this problem: a construction algorithm, a shaping algorithm, and a comparison algorithm. The algorithms for discovering all functional discrepancies between two given firewall policies can be used to perform firewall policy change impact analysis as well. Firewall policies often need to be changed, as networks evolve, and new threats emerge. Many firewall policy errors are caused by the unintended side effects of policy changes. Our algorithms can be used directly to compute the impact of firewall policy changes by computing the functional discrepancies between the policy before changes and the policy after changes. [ABSTRACT FROM AUTHOR]

The paper presents a detailed discussion of various issues involved in designing a medium access control (MAC) protocol for multihop wireless networks with nodes employing multiple beam smart antennas. Multiple beam smart antennas can form several beams simultaneously and can initiate concurrent transmissions or receptions in them, thereby increasing the throughput of the bottleneck nodes. Traditional on-demand MAC protocols for omnidirectional and single beam directional antennas based on the IEEE 802.11 distributed coordination function (DCF) mechanism cannot take advantage of this unique capability of multiple beam antennas as they do not facilitate concurrent transmissions or receptions by a node. This paper introduces a novel protocol, hybrid MAC .(HMAC), which enables concurrent packet reception (CPR) and concurrent packet transmission (CPT) at a node equipped with multiple beam antennas and is backward compatible with IEEE 802.11 DCF. Simulation results show the superior performance of HMAC in most ad hoc scenarios. Moreover, in some sample topologies, the throughput of HMAC is close to the theoretical maximum. The paper also presents a wireless mesh network architecture with heterogeneous antenna technologies and illustrates the advantages of employing multiple beam smart antennas and HMAC in such networks. [ABSTRACT FROM AUTHOR]

In recent years, inspired by the emerging Web services standard and peer-to-peer technology, a new federated service providing (FSP) system paradigm has attracted increasing research interests. Many existing systems have either explicitly or implicitly followed this paradigm. Instead of exchanging files, peers in FSP systems share their computation resources in order to offer domain specific services. In this paper, we focused on the coordination problem of how to self-organize the service group structures in response to the varying service demand. We presented our solution in the form of a coordination mechanism, which includes a labor- market model, a recruiting protocol, and a policy-driven decision architecture. Peers make their service providing decisions based on their local policies, which can be added, removed, or modified by users. A general methodology is introduced in this paper to facilitate policy design. Specifically, a heuristic inspired by the Extremal Optimization technique is utilized to handle potential inconsistencies among policies. A stimulus-response mechanism was further applied to make the decision process adjustable. Experiments under five application scenarios verified our ideas and demonstrated the effectiveness of our coordination mechanism. [ABSTRACT FROM AUTHOR]

The topology of a network may change inevitably, due to dynamic behaviors of nodes and links, and failures of hardware and software. Many protocols and applications must be aware of the up-to-date topology of the underlying network. This triggers the topology calibration problem, which means to deduce those different nodes and links between two topologies. The Bloom filter and its variants are efficient to represent and calibrate two general sets. They, however, fail to represent all links and nodes in a topology simultaneously, and thus remain inapplicable to the topology calibration problem. In this paper, we design the graph filter, a novel space-efficient data structure to record not only the node set but also the link set of any given topology. Accordingly, given two topologies we aim to represent them via two respective graph filters, and thereafter deduce those different links in an invertible manner. To this end, we design three essential operations for graph filter, i.e., encoding, subtracting and decoding. Although such operations are sufficient to solve the topology calibration problem, two challenging issues still remain open. First, the XOR traps which occur with low probability at the encoding stage may result in a few miscalculations at the decoding stage. Thus, we propose another augmented decoding algorithm to lessen the impact of XOR traps via terminating illegal decodings. Second, several different links may form cycles in the worst case; hence, we further design a cycle destruction algorithm to make such different links decodable. We implement the graph filter and the associated topology calibration method. Comprehensive evaluations indicate that our method finishes the topology calibration task efficiently with high probability, incurs the least space overhead, and supports invertible decoding reasonably. [ABSTRACT FROM AUTHOR]

Size-based routing provides robust strategies to improve the performance of computer and communication systems with highly variable workloads because it is able to isolate small jobs from large ones in a static manner. The basic idea is that each server is assigned all jobs whose sizes belong to a distinct and continuous interval. In the literature, dispatching rules of this type are referred to as SITA (Size Interval Task Assignment) policies. Though their evident benefits, the problem of finding a SITA policy that minimizes the overall mean (steady-state) waiting time is known to be intractable. In particular it is not clear when it is preferable to balance or unbalance server loads and, in the latter case, how. In this paper, we provide an answer to these questions in the celebrated limiting regime where the system capacity grows linearly with the system demand to infinity. Within this framework, we prove that the minimum mean waiting time achievable by a SITA policy necessarily converges to the mean waiting time achieved by SITA-E, the SITA policy that equalizes server loads, provided that servers are homogeneous. However, within the set of SITA policies we also show that SITA-E can perform arbitrarily bad if servers are heterogeneous. In this case we prove that there exist exactly $C!$C! asymptotically optimal policies, where $C$C denotes the number of server types, and all of them are linked to the solution of a single strictly convex optimization problem. It turns out that the mean waiting time achieved by any of such asymptotically optimal policies does not depend on how job-size intervals are mapped to servers. Our theoretical results are validated by numerical simulations with respect to realistic parameters and suggest that the above insights are also accurate in small systems composed of a few servers, i.e., ten. [ABSTRACT FROM AUTHOR]

This paper is concerned with a particular family of regular 4-connected graphs, called chordal rings. Chordal rings are a variation of ring networks. By adding two extra links (or chords) at each vertex in a ring network, the reliability and fault-tolerance of the network are enhanced. Two spanning trees on a graph are said to be independent if they are rooted at the same vertex, say, r, and for each vertex v ≠ r, the two paths from r to v, one path in each tree, are internally disjoint. A set of spanning trees on a given graph is said to be independent if they are pairwise independent. Iwasaki et al. [9] proposed a linear time algorithm for finding four independent spanning trees on a chordal ring. In this paper, we give a new linear time algorithm to generate four independent spanning trees with a reduced height in each tree. Moreover, a complete analysis of our improvements on the heights of independent spanning trees is also provided. [ABSTRACT FROM AUTHOR]

Twisted cubes are variants of hypercubes. In this paper, we study the optimal embeddings of paths of all possible lengths between two arbitrary distinct nodes in twisted cubes. We use TQn to denote the n-dimensional twisted cube and use dist(TQn, u, υ) to denote the distance between two nodes u and υ in TQn, where n ≥ 1 is an odd integer. The original contributions of this paper are as follows: 1) We prove that a path of length l can be embedded between u and υ with dilation 1 for any two distinct nodes u and υ and any integer l with dist(TQn, u, υ) + 2 ≤ l ≤ 2n - 1 (n ≥ 3) and 2) we find that there exist two nodes u and υ such that no path of length dist(TQn, u, υ) + 1 can be embedded between n and υ with dilation 1 (n ≥ 3). The special cases for the nonexistence and existence of embeddings of paths between nodes u and υ and with length dist(TQn, u, υ) + 1 are also discussed. The embeddings discussed in this paper are optimal in the sense that they have dilation 1. [ABSTRACT FROM AUTHOR]

Probabilistic inference was shown effective in the nondeterministic diagnosis of end-to-end service failures when applied in a centralized management system where the manager possesses a global knowledge of the system structure and state. Since many networks are organized into multiple administrative domains that may be unable to share configuration and state information, these centralized techniques are not applicable to them. This paper proposes a fault localization technique suitable for multidomain networks with hierarchical routing. The proposed technique divides the computational effort and system knowledge among multiple, hierarchically organized managers. Each manager performs fault localization in the domain it manages and requires only the knowledge of its own domain. We show through simulation that the proposed approach not only improves the feasibility of fault localization in multidomain networks, but also increases the effectiveness of probabilistic diagnosis and makes it realizable in networks of considerable size. [ABSTRACT FROM AUTHOR]

Transparent data replication is a promising technique for improving the system performance of a large distributed network. Transcoding is an important technology which adapts the same multimedia object to diverse mobile appliances; thus, users' requests for a specified version of a multimedia object could be served by a more detailed version cached according to transcoding. Therefore, it is particularly of theoretical and practical necessity to determine the proper version to be cached at each node such that the specified objective is achieved. In this paper, we address the problem of multimedia object placement for transparent data replication. The performance objective is to minimize the total access cost by considering both transmission cost and transcoding cost. We present optimal solutions for different cases for this problem. The performance of the proposed solutions is evaluated with a set of carefully designed simulation experiments for various performance metrics over a wide range of system parameters. The simulation results show that our solution consistently and significantly outperforms comparison solutions in terms of all the performance metrics considered. [ABSTRACT FROM AUTHOR]

Most of the current communication networks, including the Internet, are packet switched networks. One of the main reasons behind the success of packet switched networks is the possibility of performance gain due to multiplexing of network bandwidth. The multiplexing gain crucially depends on the size of the buffers available at the nodes of the network to store packets at the congested links. However, most of the previous work assumes the availability of infinite buffer-size. In this paper, we study the effect of finite buffer-size on the performance of networks of interacting queues. In particular, we study the throughput of flow-controlled loss-less networks with finite buffers. The main result of this paper is the characterization of a dynamic scheduling policy that achieves the maximal throughput with a minimal finite buffer at the internal nodes of the network under memory-less (e.g., Bernoulli IID) exogenous arrival process. However, this ideal performance policy is rather complex and, hence, difficult to implement. This leads us to the design of a simpler and possibly implementable policy. We obtain a natural trade-off between throughput and buffer-size for such implementable policy. Finally, we apply our results to packet switches with buffered crossbar architecture. [ABSTRACT FROM AUTHOR]

Perfect difference networks (PDNs) that are based on the mathematical notion of perfect difference sets have been shown to comprise an asymptotically optimal method for connecting a number of nodes into a network with diameter 2. Justifications for, and mathematical underpinning of, PDNs appear in a companion paper. In this paper, we compare PDNs and some of their derivatives to interconnection networks with similar cost/performance, including certain generalized hypercubes and their hierarchical variants. Additionally, we discuss point-to-point and collective communication algorithms and derive a general emulation result that relates the performance of PDNs to that of complete networks as ideal benchmarks. We show that PDNs are quite robust, both with regard to node and link failures that can be tolerated and in terms of blandness (not having weak spots). In particular, we prove that the fault diameter of PDNs is no greater than 4. Finally, we study the complexity and scalability aspects of these networks, concluding that PDNS and their derivatives allow the construction of very low diameter networks close to any arbitrary desired size and that, in many respects, PDNs offer optimal performance and fault tolerance relative to their complexity or implementation cost. [ABSTRACT FROM AUTHOR]

In view of their applicability to parallel and distributed computer systems, interconnection networks have been studied intensively by mathematicians, computer scientists, and computer designers. ln this paper, we propose an asymptotically optimal method for connecting a set of nodes into a perfect difference network (PDN) with diameter 2, so that any node is reachable from any other node in one or two hops. The PDN interconnection scheme, which is based on the mathematical notion of perfect difference sets, is optimal in the sense that it can accommodate an asymptotically maximal number of nodes with smallest possible node degree under the constraint of the network diameter being 2. We present the network architecture in its basic and bipartite forms and show how the related multidimensional PDNs can be derived. We derive the exact average internode distance and tight upper and lower bounds for the bisection width of a PDN. We conclude that PDNs and their derivatives constitute worthy additions to the repertoire of network designers and may offer additional design points that can be exploited by current and emerging technologies, including wireless and optical interconnects. Performance, algorithmic, and robustness attributes of PDNs are analyzed in a companion paper. [ABSTRACT FROM AUTHOR]

Parallel and distributed systems may operate in an environment that undergoes unpredictable changes causing certain system performance features to degrade. Such systems need robustness to guarantee limited degradation despite fluctuations in the behavior of its component parts or environment. This research investigates the robustness of an allocation of resources to tasks in parallel and distributed systems. The main contributions of this paper are 1) a mathematical description of a metric for the robustness of a resource allocation with respect to desired system performance features against multiple perturbations in multiple system and environmental conditions, and 2) a procedure for deriving a robustness metric for an arbitrary system. For illustration, this procedure is employed to derive robustness metrics for three example distributed systems. Such a metric can help researchers evaluate a given resource allocation for robustness against uncertainties in specified perturbation parameters. [ABSTRACT FROM AUTHOR]

There is a growing demand for network support for group applications, in which messages from one or more sender(s) are delivered to a large number of receivers. In this paper, we propose a network architecture for supporting a fundamental type of group communication, conferencing. A conference refers to a group of members in a network who communicate with each other within the group. We consider adopting a class of multistage networks, such as a baseline, an omega, or an indirect binary cube network, composed of switch modules with fan-in and fan-out capability for a conference network which supports multiple disjoint conferences. The key issue in designing a conference network is to determine the multiplicity of routing conflicts, which is the maximum number of conflict parties competing a single interstage link when multiple disjoint conferences simultaneously present in the network. Our results in this paper show that, for a network of size n × n, the multiplicities of routing conflicts are small constants (between 2 and 4) for an omega network or an indirect binary cube network; while it can be as large as &frac&radicn;q; + 1 for a baseline network, where q is the minimum allowable conference size. Thus, our design for conference networks is based on an omega network or an indirect binary cube network. We also develop fast self-routing algorithms for setting up routing paths in the newly designed conference networks. As can be seen, such an it x it conference network has O(n Iog n) routing time and communication delay and O(n log n) hardware cost. The conference networks are superior to existing designs in terms of routing complexity, communication delay and hardware cost. The conference network proposed is rearrangeably nonblocking in general, and is strictly nonblocking under some conference service policy. It can be used in applications that require efficient or real-time group communication. [ABSTRACT FROM AUTHOR]

Distributed file searching in delay tolerant networks formed by mobile devices can potentially support various useful applications. In such networks, nodes often present certain social network properties of their holders in terms of contents (i.e., interests) and contacts. However, current methods in DTNs only consider either content or contact for file searching or dissemination, which limits the file sharing efficiency. In this paper, we first analyze real traces to confirm the importance and necessity of considering both content and contact in file search. We then propose Cont2, a social-aware file search method that exploits both node contents and contact patterns. First, considering people with common interests tend to share files and gather together, Cont2 virtually groups common-interest nodes into a community to direct file search. Second, considering human mobility follows a certain pattern, Cont2 exploits nodes' contact frequencies with a community to expedite file searching. To further improve the searching efficiency, Cont2 also integrates sub-communities and parallel forwarding as optional components for file searching. Trace-driven experiments on the GENI testbed and NS-2 simulator show that Cont2 can effectively improve the search efficiency compared to current methods. [ABSTRACT FROM AUTHOR]

Router's buffer design and management strongly influence energy, area and performance of on-chip networks, hence it is crucial to encompass all of these aspects in the design process. At the same time, the NoC design cannot disregard preventing network-level and protocol-level deadlocks by devoting ad-hoc buffer resources to that purpose. In chip multiprocessor systems the coherence protocol usually requires different virtual networks (VNETs) to avoid deadlocks. Moreover, VNET utilization is highly unbalanced and there is no way to share buffers between them due to the need to isolate different traffic types. This paper proposes CUTBUF, a novel NoC router architecture to dynamically assign virtual channels (VCs) to VNETs depending on the actual VNETs load to significantly reduce the number of physical buffers in routers, thus saving area and power without decreasing NoC performance. Moreover, CUTBUF allows to reuse the same buffer for different traffic types while ensuring that the optimized NoC is deadlock-free both at network and protocol level. In this perspective, all the VCs are considered spare queues not statically assigned to a specific VNET and the coherence protocol only imposes a minimum number of queues to be implemented. Synthetic applications as well as real benchmarks have been used to validate CUTBUF , considering architectures ranging from 16 up to 48 cores. Moreover, a complete RTL router has been designed to explore area and power overheads. Results highlight how CUTBUF can reduce router buffers up to 33 percent with 2 percent of performance degradation, a 5 percent of operating frequency decrease and area and power saving up to 30.6 and 30.7 percent, respectively. Conversely, the flexibility of the proposed architecture improves by 23.8 percent the performance of the baseline NoC router when the same number of buffers is used. [ABSTRACT FROM PUBLISHER]

In this paper we study energy conservation in the Internet. We observe that different traffic volumes on a link can result in different energy consumption; this is mainly due to such technologies as trunking (IEEE 802.1AX), adaptive link rates, etc. We design a green Internet routing scheme, where the routing can lead traffic in a way that is green. We differ from previous studies where they switch network components, such as line cards and routers, into sleep mode. We do not prune the Internet topology. We first develop a power model, and validate it using real commercial routers. Instead of developing a centralized optimization algorithm, which requires additional protocols such as MPLS to materialize in the Internet, we choose a hop-by-hop approach. It is thus much easier to integrate our scheme into the current Internet. We progressively develop three algorithms, which are loop-free, substantially reduce energy consumption, and jointly consider green and QoS requirements such as path stretch. We further analyze the power saving ratio, the routing dynamics, and the relationship between hop-by-hop green routing and QoS requirements. We comprehensively evaluate our algorithms through simulations on synthetic, measured, and real topologies, with synthetic and real traffic traces. We show that the power saving in the line cards can be as much as 50 percent. [ABSTRACT FROM AUTHOR]

Scalable, low-latency and accurate RFID counting algorithms have recently been proposed as a fundamental building block to support more complex query operations in a large-scale RFID system. One distinct feature of these algorithms is that they do not require explicit identification of individual tags and therefore can eliminate the latency bottleneck caused by serialization during multiple access control. However, these algorithms all assume reliable communications between the reader and the tags. While this assumption is also adopted by many tag-identification protocols in the current RFID standards, it is practically unachievable given the current technology and low-cost requirement of RFID tags. In fact, recent empirical studies have found that the communication between an RFID reader and a set of seemingly “in-range” tags are still unreliable and highly non-deterministic due to the varying channel conditions. In this paper, we discuss the design and performance analysis of a set of channel-oblivious RFID counting algorithms which can estimate the size of a tag-set of interest over unreliable wireless channels. The proposed schemes can provide accurate cardinality estimates without any prior knowledge of the channel parameters. We first propose a series of algorithms and analyze their performance under a simplified memoryless lossy channel model. We then extend them to handle the impact due to backscattering effects and correlated losses found in practical RFID systems. Our proposed designs only require simple modifications to standard RFID tags and readers and can be implemented using current technologies with minimal increase in tag/ reader cost. Our designs can also be extended to other RFID counting algorithms which assumed reliable communication channels. [ABSTRACT FROM AUTHOR]

Virtual machine migration has been touted as one of the crucial technologies in improving data center efficiency, such as reducing energy cost and maintaining load balance. However, traditional approaches could not avoid the service interruption completely. Moreover, they often result in longer delay and are prone to failures. In this paper, we leverage the emerging named data networking (NDN) to design an efficient and robust protocol to support seamless virtual machine migration in cloud data center. Specifically, virtual machines (VMs) are named with the services they provide. Request routing is based on service names instead of IP addresses that are normally bounded with physical machines. As such, services would not be interrupted when migrating supported VMs to different physical machines. We further analyze the performance of our proposed NDN-based VM migration protocol, and optimize its performance via a load balancing algorithm. Our extensive evaluations verify the effectiveness and the efficiency of our approach and demonstrate that it is interruption-free. [ABSTRACT FROM AUTHOR]

Recently, the content-based publish/subscribe (pub/sub) paradigm has been gaining popularity in opportunistic mobile networks (OppNets) for its flexibility and adaptability. Since nodes in OppNets are controlled by humans, they often behave selfishly. Therefore, stimulating nodes in selfish OppNets to collect, store, and share contents efficiently is one of the key challenges. Meanwhile, guaranteeing the freshness of contents is also a big problem for content dissemination in OppNets. In this paper, in order to solve these problems, we propose an incentive-driven and freshness-aware pub/sub Content Dissemination scheme, called ConDis, for selfish OppNets. In ConDis, the Tit-For-Tat (TFT) scheme is employed to deal with selfish behaviors of nodes in OppNets. Moreover, a novel content exchange protocol is proposed when nodes are in contact. Specifically, during each contact, the exchange order is determined by the content utility, which represents the usefulness of a content for a certain node, and the objective of nodes is to maximize the utility of the content inventory stored in their buffer. Extensive realistic trace-driven simulation results show that ConDis is superior to other existing schemes in terms of total freshness value, total delivered contents, and total transmission cost. [ABSTRACT FROM AUTHOR]

A major problem encountered by researchers of dynamic neural networks is the computational complexity increasing the learning time. In this paper the parallel realization of the RTRN and the Elman networks are discussed. Both networks are examples of dynamic neural networks. Inherent parallelism of dynamic neural networks has been employed to accelerate the learning process. The proposed solution is based on a highly parallel three dimensional architecture to speed up the learning performance. The presented structures are suitable for efficient parallel realization in digital hardware or vector processors. [ABSTRACT FROM AUTHOR]

NUCA caches have traditionally been proposed as a solution for mitigating wire delays, and delays introduced due to complex networks on chip. Traditional approaches have reported significant performance gains with intelligent block placement, location, replication, and migration schemes. In this paper, we propose a novel approach in this space, called FP-NUCA. It differs from conventional approaches, and relies on a novel method of co-designing the last level cache and the network on chip. We artificially constrain the communication pattern in the NUCA cache such that all the messages travel along a few predefined paths (fast paths) for each set of banks. We leverage this communication pattern by designing a new type of NOC router called the Freeze router, which augments a regular router by adding a layer of circuitry that gates the clock of the regular router when there is a fast path message waiting to be transmitted. Messages along the fast path do not require buffering, switching, or routing. We incorporate a bank predictor with our novel NOC for reducing the number of messages, and resultant energy consumption. We compare our performance with state of the art protocols, and report speedups of up to 31 percent (mean: 6.3 percent), and $ED^2$ reduction up to 46 percent (mean: 10.4 percent) for a suite of Splash and Parsec benchmarks. We implement the Freeze router in VHDL and show that the additional fast path logic has minimal area and timing overheads. [ABSTRACT FROM AUTHOR]

Neighbor discovery is one of the first steps in configuring and managing a wireless network. Most existing studies on neighbor discovery assume a single-packet reception model where only a single packet can be received successfully at a receiver. In this paper, motivated by the increasing prevalence of multipacket reception (MPR) technologies such as CDMA and MIMO, we study neighbor discovery in MPR networks that allow packets from multiple simultaneous transmitters to be received successfully at a receiver. Starting with a clique of n nodes, we first analyze a simple Aloha-like algorithm and show that it takes \Theta ({ n \;\ln \;n\over k}) time to discover all neighbors with high probability when allowing up to k$ simultaneous transmissions. We then design two adaptive neighbor discovery algorithms that dynamically adjust the transmission probability for each node. We show that the adaptive algorithms yield a \Theta (\ln \;n)$ improvement over the Aloha-like scheme for a clique with n$ nodes and are thus order-optimal. Finally, we analyze our algorithms in a general multi-hop network setting. We show an upper bound of for the Aloha-like algorithm when the maximum node degree is \Delta$, which is at most a factor \ln \;n$ worse than the optimal. In addition, when \Delta which matches the lower bound for the problem. [ABSTRACT FROM PUBLISHER]

Coverage of interest points and network connectivity are two main challenging and practically important issues of Wireless Sensor Networks (WSNs). Although many studies have exploited the mobility of sensors to improve the quality of coverage andconnectivity, little attention has been paid to the minimization of sensors’ movement, which often consumes the majority of the limited energy of sensors and thus shortens the network lifetime significantly. To fill in this gap, this paper addresses the challenges of the Mobile Sensor Deployment (MSD) problem and investigates how to deploy mobile sensors with minimum movement to form a WSN that provides both target coverage and network connectivity. To this end, the MSD problem is decomposed into two sub-problems: the Target COVerage (TCOV) problem and the Network CONnectivity (NCON) problem. We then solve TCOV and NCON one by one and combine their solutions to address the MSD problem. The NP-hardness of TCOV is proved. For a special case of TCOV where targets disperse from each other farther than double of the coverage radius, an exact algorithm based on the Hungarian method is proposed to find the optimal solution. For general cases of TCOV, two heuristic algorithms, i.e., the Basic algorithm based on clique partition and the TV-Greedy algorithm based on Voronoi partition of the deployment region, are proposed to reduce the total movement distance ofsensors. For NCON, an efficient solution based on the Steiner minimum tree with constrained edge length is proposed. Thecombination of the solutions to TCOV and NCON, as demonstrated by extensive simulation experiments, offers a promising solutionto the original MSD problem that balances the load of different sensors and prolongs the network lifetime consequently. [ABSTRACT FROM AUTHOR]

Fat trees are considered suitable structures for data center interconnection networking. Such structures are rigid, and hard to scale up and scale out. A good data center network structure should have high scalability, efficient switch utilization, and high reliability. In this paper we present a class of data center network structures based on hypergraph theory and combinatorial block design theory. We show that our data center network structures are more flexible and scalable than fat trees. Using switches of the same size, our data center network structures can connect more nodes than fat trees, and it is possible to construct different structures with tradeoffs among inter-cluster communication capacity, reliability, the number of switches used, and the number of connected nodes. [ABSTRACT FROM AUTHOR]

Network lifetime maximization with guaranteed coverage is an important issue in wireless sensor networks. Based on our recently proposed confident information coverage (CIC) model, this paper studies the multi-modal confident information coverage (M2CIC) problem. Assuming that each node is equipped with different types of sensors, the objective is to schedule the multi-modal sensors’ activity, such that the confident information coverage for each sensing modality can be guaranteed while the network lifetime can be maximized. We model the M2CIC problem as a multi-modal set cover problem (M2SC) and prove its NP-completeness. For solving the M2SC problem, we design two energy-efficient heuristics including a centralized one and a distributed one. In the proposed algorithms, different modal sensors are organized into a family of set covers, each of which can provide confident information coverage for all the monitored physical phenomena. Simulation results show that both the proposed algorithms can efficiently prolong the network lifetime and outperform two classical peer algorithms in terms of the extended network lifetime. [ABSTRACT FROM AUTHOR]

How to precisely measure performance of routing algorithm is an important issue when studying routing algorithm of network-on-chip (NoC). The degree of adaptiveness is the most widely used metric in the literature. However, our study shows that the degree of adaptiveness cannot precisely measure performance of routing algorithm. It cannot account for why routing algorithm with high degree of adaptiveness may have poor performance. Simulation has to be carried out to evaluate performance of routing algorithm. In this paper, we propose a new metric of routing pressure for measuring performance of routing algorithm. It has higher precision of measuring routing algorithm performance than the degree of adaptiveness. Performance of routing algorithm can be evaluated through routing pressure without simulation. It can explain why congestion takes place in network. In addition, where and when congestion takes place can be pointed out without simulation. [ABSTRACT FROM AUTHOR]

To disseminate messages from a single source to a large number of targeted receivers, a natural approach is the tree-based application layer multicast (ALM). In time-constrained flash dissemination scenarios, e.g. earthquake early warning, where time is of the essence, the reliable extensions of the tree-based ALM using ack-based failure recovery protocols cannot support reliable dissemination in the timeframe needed. In this paper, we propose FaReCast which exploits path diversity, i.e., exploit the use of multiple data paths, to achieve fast and reliable data dissemination. First, we design a forest-based M2M (Multiple parents-To-Multiple children) ALM structure where every node has multiple children and multiple parents. The intuition is to enable lower dissemination latency through multiple children, while enabling higher reliability through multiple parents. In order to maintain the M2M ALM structure in a scalable and reliable manner, we develop a DHT-based Distributed Configuration Manager. Second, we design multidirectional multicasting algorithms that effectively utilize the multiple data paths in the M2M ALM structure. A key aspect of our reliable dissemination mechanism is that nodes, in addition to communicating the data to children, also selectively disseminate the data to parents and siblings. As compared to trees using traditional multicasting algorithm, we observe an 80 percent improvement in reliability under 20 percent of failed nodes with no significant increase in latency for over 99 percent of the nodes. Moreover, we notice that FaReCast can reduce the network overhead more than 50 percent by tuning the M2M structure, as compared to the other reliable ALM based disseminations. [ABSTRACT FROM AUTHOR]

Content distribution networks (CDNs) built on clouds have recently started to emerge. Compared to conventional CDNs, cloud-based CDNs have the benefit of cost efficient hosting services without owning infrastructure. However, resource provisioning and replica placement in cloud CDNs involve a number of challenging issues, mainly due to the dynamic nature of demand patterns. To deal with this dynamic nature, this paper proposes a set of novel algorithms to solve the joint problem of resource provisioning and caching (i.e., replica placement) for cloud-based CDNs with an emphasis on handling the dynamic demand patterns. Firstly, we propose a provisioning and caching algorithm framework called Differential Provisioning and Caching (DPC) algorithm, which aims to rent cloud resources to build CDNs and whereby to cache contents so that the total rental cost can be minimized while all demands are served. DPC consists of 2 steps. Step 1 first maximizes total demands supported by unexpired resources. Then, step 2 minimizes the total rental cost for new resources to serve all remaining demands. For each step we design both greedy and iterative heuristics, each with different advantages over the existing approaches. Moreover, to dynamically adjusts the placement of contents and route maps, we further propose the Caching and Request Balancing (CRB) algorithm, which is light-weight and thus can be frequently executed as a companion of DPC to maximize the total demands. Performance evaluation results are presented to demonstrate the effectiveness and competitiveness of our approaches when compared to existing algorithms. [ABSTRACT FROM PUBLISHER]

In this paper, a game-theoretical framework for the design of distributed algorithms that control the transmission range (TR) of nodes in order to maximize throughput in Wireless Multihop Networks (WMN) is proposed. It is based on the stability region of the link-scheduling policy adopted for the network. The stability region is defined as the set of input-packet rates under which the queues in the network are stable (i.e., positive recurrent). The goal of the TR-control algorithms is to adapt the stability region to a given set of end-to-end flows. In the algorithms, the flows control distributively the nodes' TRs using the stability region in order to enable higher end-to-end packet rates while guaranteeing stability. In order to demonstrate how the algorithms can be designed using the proposed game-theoretical framework, a new TR-control algorithm for IEEE-802.16 WMNs is developed. Its convergence is demonstrated, and a performance bound is calculated. Finally, simulation results show that the algorithm is able to find the optimal TRs more effectively. The TRs achieve throughput levels that are at least 90 percent of the optimal throughput for 72 percent of the simulated scenarios, whereas the classic approach of spatial-reuse maximization does this for 62 percent of the scenarios. [ABSTRACT FROM AUTHOR]

Network virtualization has emerged as a promising approach to overcome the ossification of the Internet. A major challenge in network virtualization is the so-called virtual network embedding problem, which deals with the efficient embedding of virtual networks with resource constraints into a shared substrate network. A number of heuristics have been proposed to cope with the NP-hardness of this problem; however, all of the existing proposals reserve fixed resources throughout the entire lifetime of a virtual network. In this paper, we re-examine this problem with the position that time-varying resource requirements of virtual networks should be taken into consideration, and we present an opportunistic resource sharing-based mapping framework, ORS, where substrate resources are opportunistically shared among multiple virtual networks. We formulate the time slot assignment as an optimization problem; then, we prove the decision version of the problem to be NP-hard in the strong sense. Observing the resemblance between our problem and the bin packing problem, we adopt the core idea of first-fit and propose two practical solutions: first-fit by collision probability (CFF) and first-fit by expectation of indicators' sum (EFF). Simulation results show that ORS provides a more efficient utilization of substrate resources than two state-of-the-art fixed-resource embedding schemes. [ABSTRACT FROM AUTHOR]

In this paper, we consider the setting of large-scale distributed systems, in which each node needs to quickly process a huge amount of data received in the form of a stream that may have been tampered with by an adversary. In this situation, a fundamental problem is how to detect and quantify the amount of work performed by the adversary. To address this issue, we propose a novel algorithm AnKLe for estimating the Kullback-Leibler divergence of an observed stream compared with the expected one. AnKLe combines sampling techniques and information-theoretic methods. It is very efficient, both in terms of space and time complexities, and requires only a single pass over the data stream. We show that AnKLe is an $((\varepsilon,\delta ))$-approximation algorithm with a space complexity $(\tilde{{\cal O}}({1\over \varepsilon } +{1\over \varepsilon^2} ))$ bits in "mostâ' cases, and $(\tilde{{\cal O}}({1\over \varepsilon } +{n-\varepsilon^{-1}\over \varepsilon^2} )) otherwise, where (n) is the number of distinct data items in a stream. Moreover, we propose a distributed version of AnKLe that requires at most ({\cal O}(r\ell (\log {n} + 1)))$ bits of communication between the $(\ell)$ participating nodes, where $(r)$ is number of rounds of the algorithm. Experimental results show that the estimation provided by AnKLe remains accurate even for different adversarial settings for which the quality of other methods dramatically decreases. [ABSTRACT FROM AUTHOR]