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We provide a framework to analyze multi-level checkpointing protocols, by formally defining a k -level checkpointing pattern. We provide a first-order approximation to the optimal checkpointing period, and show that the corresponding overhead is in the order of \sum _{\ell =1}^{k}\sqrt{2\lambda _\ell C_\ell} , where \lambda _\ell$ is the error rate at level  $\ell$ , and $C_\ell$ the checkpointing cost at level $\ell$ . This nicely extends the classical Young/Daly formula on single-level checkpointing. Furthermore, we are able to fully characterize the shape of the optimal pattern (number and positions of checkpoints), and we provide a dynamic programming algorithm to determine the optimal subset of levels to be used. Finally, we perform simulations to check the accuracy of the theoretical study and to confirm the optimality of the subset of levels returned by the dynamic programming algorithm. The results nicely corroborate the theoretical study, and demonstrate the usefulness of multi-level checkpointing with the optimal subset of levels. [ABSTRACT FROM AUTHOR]

With the rapid proliferation of RFID technologies, RFID has been introduced into applications such as inventory and sampling inspection. Conventionally, in RFID systems, the reader usually identifies all the RFID tags in the interrogation region with the maximum power. However, some applications may only need to identify the tags in a specified area, which is usually smaller than the reader’s default interrogation region. An example could be identifying the tags in a box, while ignoring the tags out of the box. In this paper, we respectively present two solutions to identify the tags in the specified area. The principle of the solutions can be compared to the picture-taking process of an auto-focus camera, which firstly focuses on the target automatically and then takes the picture. Similarly, our solutions first focus on the specified area and then shoot the tags. The design of the two solutions is based on the extensive empirical study on RFID tags. Realistic experiment results show that our solutions can reduce the execution time by $44$ percent compared to the baseline solution, which identifies the tags with maximum power. Furthermore, we improve the proposed solutions to make them work well in more complex environments. [ABSTRACT FROM AUTHOR]

We propose algorithms for distributing the classifier rules to two ternary content addressable memories (TCAMs) and for incrementally updating the TCAMs. The performance of our scheme is compared against the prevalent scheme of storing classifier rules in a single TCAM in priority order. Our scheme results in an improvement in average lookup speed by up to 49% and an improvement in update performance by up to 3.84 times in terms of the number of TCAM writes. [ABSTRACT FROM AUTHOR]

We consider Internet-based master-worker computations, where a master processor assigns, across the Internet, a computational task to a set of untrusted worker processors, and collects their responses. Examples of such computations are the "@homeâ' projects such as SETI. In this work, various worker behaviors are considered. Altruistic workers always return the correct result of the task, malicious workers always return an incorrect result, and rational workers act based on their self-interest. In a massive computation platform, such as the Internet, it is expected that all three type of workers coexist. Therefore, in this work, we study Internet-based master-worker computations in the presence of malicious, altruistic, and rational workers. A stochastic distribution of the workers over the three types is assumed. In addition, we consider the possibility that the communication between the master and the workers is not reliable, and that workers could be unavailable. Considering all the three types of workers renders a combination of game-theoretic and classical distributed computing approaches to the design of mechanisms for reliable Internet-based computing. Indeed, in this work, we design and analyze two algorithmic mechanisms to provide appropriate incentives to rational workers to act correctly, despite the malicious workers' actions and the unreliability of the communication. Only when necessary, the incentives are used to force the rational players to a certain equilibrium (which forces the workers to be truthful) that overcomes the attempt of the malicious workers to deceive the master. Finally, the mechanisms are analyzed in two realistic Internet-based master-worker settings, a SETI-like one and a contractor-based one, such as Amazon's mechanical turk. We also present plots that illustrate the tradeoffs between reliability and cost, under different system parameters. [ABSTRACT FROM AUTHOR]

In large-scale Wireless Sensor Networks (WSNs), leveraging data sinks' mobility for data gathering has drawn substantial interests in recent years. Current researches either focus on planning a mobile sink's moving trajectory in advance to achieve optimized network performance, or target at collecting a small portion of sensed data in the network. In many application scenarios, however, a mobile sink cannot move freely in the deployed area. Therefore, the precalculated trajectories may not be applicable. To avoid constant sink location update traffics when a sink's future locations cannot be scheduled in advance, we propose two energy-efficient proactive data reporting protocols, SinkTrail and SinkTrail-S, for mobile sink-based data collection. The proposed protocols feature low-complexity and reduced control overheads. Two unique aspects distinguish our approach from previous ones: 1) we allow sufficient flexibility in the movement of mobile sinks to dynamically adapt to various terrestrial changes; and 2) without requirements of GPS devices or predefined landmarks, SinkTrail establishes a logical coordinate system for routing and forwarding data packets, making it suitable for diverse application scenarios. We systematically analyze the impact of several design factors in the proposed algorithms. Both theoretical analysis and simulation results demonstrate that the proposed algorithms reduce control overheads and yield satisfactory performance in finding shorter routing paths. [ABSTRACT FROM AUTHOR]

The IEEE P1687 (IJTAG) standard proposal aims at providing a standardized interface between the IEEE Standard 1149.1 test access port (TAP) and on-chip embedded test, debug and monitoring logic (instruments), such as scan chains and temperature sensors. A key feature in P1687 is to include Segment Insertion Bits (SIBs) in the scan path to allow flexibility both in designing the instrument access network and in scheduling the access to instruments. This paper presents algorithms to compute the overall access time (OAT) for a given P1687 network. The algorithms are based on analysis for flat and hierarchical network architectures, considering two access schedules, i.e., concurrent schedule and sequential schedule. In the analysis, two types of overhead are identified, i.e., network configuration data overhead and JTAG protocol overhead. The algorithms are implemented and employed in a parametric analysis and in experiments on realistic industrial designs. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) architectures are popular for tasks such as collaborative download, VoIP telephony, and backup. To maximize performance in the face of widely variable storage capacities and bandwidths, such systems typically need to shift work from poor nodes to richer ones. Similar requirements are seen in today's large data centers, where machines may have widely variable configurations, loads, and performance. In this paper, we consider the slicing problem, which involves partitioning the participating nodes into κ subsets using a one-dimensional attribute, and updating the partition as the set of nodes and their associated attributes change. The mechanism thus facilitates the development of adaptive systems. We begin by motivating this problem statement and reviewing prior work. Existing algorithms are shown to have problems with convergence, manifesting as inaccurate slice assignments, and to adapt slowly as conditions change. Our protocol, Sliver, has provably rapid convergence, is robust under stress and is simple to implement. We present both theoretical and experimental evaluations of the protocol. [ABSTRACT FROM AUTHOR]

The establishment of a localization system is an important task in wireless sensor networks. Due to the geographical correlation between sensed data, location information is commonly used to name the gathered data and address nodes and regions in data dissemination protocols. In general, to estimate its location, a node needs the position information of at least three reference points (neighbors that know their positions). In this work, we propose a different scheme in which only two reference points are required in order to estimate a position. To choose between the two possible solutions of an estimate, we use the known direction of the recursion. This approach leads to a recursive localization system that works with low-density networks (increasing by 40 percent the number of nodes with estimates in some cases), reduces the position error by almost 30 percent, requires 37 percent less processor resources to estimate a position, uses fewer beacon nodes, and also indicates the node position error based on its distance to the recursion origin. No GPS-enabled node is required, since the recursion origin can be used as a relative coordinate system. The algorithm's evaluation is performed by comparing it with a similar localization system; also, experiments are made to evaluate the impact of both systems in geographic algorithms. [ABSTRACT FROM AUTHOR]

Let G = (V, E, w) be a simple digraph, in which all edge weights are nonnegative real numbers. Let G' be obtained from G by an application of a set of edge weight updates to G. Let s ∈ V and let Ts and T's be Shortest Path Trees (SPTs) rooted at s in G and G', respectively. The Dynamic Shortest Path (DSP) problem is to compute T's from Ts. Existing work on this problem focuses on either a single edge weight change or multiple edge weight changes in which some of them are incorrect or are not optimized. We correct and extend a few state-of-the-art dynamic SPT algorithms to handle multiple edge weight updates. We prove that these algorithms are correct. Dynamic algorithms may∙not outperform static algorithms all the time. To evaluate the proposed dynamic algorithms, we compare them with the well-known static Dijkstra algorithm. Extensive experiments are conducted with both real-life and artificial data sets. The experimental results suggest the most appropriate algorithms to be used under different circumstances. [ABSTRACT FROM AUTHOR]

A causal broadcast protocol was proposed earlier in [1]. Two extensions of the protocol were also proposed in order to improve its throughput and bandwidth utilization. In this paper, we show that both extensions are not live, i.e., there may be execution patterns in which processes stop delivering messages. We also show that the algorithm for the second extension does not satisfy the requirements on which its correctness was established. Finally, we provide fixed versions of both extensions and prove their correctness. [ABSTRACT FROM AUTHOR]

We propose a generic framework for distributed broadcasting in ad hoc wireless networks. The approach is based on selecting a small subset of nodes to form a forward node set to carry out a broadcast process. The status of each node, forward or nonforward, is determined either by the node itself or by other nodes. Node status can be determined at different snapshots of network state along time (called views) without causing problems in broadcast coverage. Therefore, the forward node set can be constructed and maintained through either a proactive process (i.e., "up-to-date") before the broadcast process or a reactive process (i.e., "on-the- fly") during the broadcast process. A sufficient condition, called coverage condition, is given for a node to take the nonforward status. Such a condition can be easily checked locally around the node. Several existing broadcast algorithms can be viewed as special cases of the generic framework with k-hop neighborhood information. A comprehensive comparison among existing algorithms is conducted. Simulation results show that new algorithms, which are more efficient than existing ones, can be derived from the generic framework. [ABSTRACT FROM AUTHOR]

In this paper, we present the performance evaluation of an algorithm for preserving temporal relationships of events in Wireless Sensor Actor Networks (WSANs). The algorithm consists of two modules, which deal with the problems of temporal event ordering and time synchronization. These two problems are approached as a whole as they complement each other: in order to temporally order the events, the nodes must be synchronized. The goal of the proposed event ordering algorithm for WSANs is to reduce the overhead in terms of energy dissipation and delay. We also propose a tunable time synchronization algorithm employing a hybrid synchronization scheme suited for clustered topology. The proposed algorithm utilizes the message exchange necessary for event ordering and routing for synchronization purposes by piggybacking messages with synchronization pulses and replies to reduce the communication cost of synchronization. Simulation experiments showed that the event ordering algorithm is capable of reducing the overhead when compared to previously proposed algorithms. The synchronization algorithm demonstrated that the combination of synchronization techniques was well suited for the communication mode utilized in a clustered topology. The approach of piggybacking synchronization pulses and replies resulted in a considerable gain, which we demonstrated in the number of messages that were piggybacked for synchronization purposes. [ABSTRACT FROM AUTHOR]

Sensing coverage is an essential functionality of wireless sensor networks (WSNs). However, it is also well known that coverage alone in WSNs is not sufficient, and hence network connectivity should also be considered for the correct operation of WSNs. In this paper, we address the problem of k-coverage in WSNs such that in each scheduling round, every location in a monitored field (or simply field) is covered by at least k active sensors while all active sensors are being connected. Precisely, we study sensors duty-cycling strategies for generating k-coverage configurations in WSNs. First, we model the k-coverage problem in WSNs. Second, we derive a sufficient condition of the sensor spatial density for complete k-coverage of a field. We also provide a relationship between the communication and sensing ranges of sensors to maintain both k-coverage of a field and connectivity among all active sensors. Third, we propose four configuration protocols to solve the problem of k-coverage in WSNs. We prove that our protocols select a minimum number of sensors to achieve full k-coverage of a field while guaranteeing connectivity between them. Then, we relax some widely used assumptions for coverage configuration in WSNs, to promote the use of our proposed protocols in real-world sensing applications. Our simulation results show that our protocols outperform an existing distributed k-coverage configuration protocol. [ABSTRACT FROM AUTHOR]