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The load-balancing method is to make the different amount of heating and cooling loads to be similar as possible for handling the more load by the balanced heat recovery (BHR) system which has higher energy performance than auxiliary system. When this method is applied, the zone set temperatures should be in comfort range and the additional energy to BHR system should not exceed the energy consumption by auxiliary system of general method. In result, the total energy consumption is lower, and some zones were more comfortable because heating or cooling set temperature was varied to the middle of comfort range. [ABSTRACT FROM AUTHOR]

Random hashing is a standard method to balance loads among nodes in Peer-to-Peer networks. However, hashing destroys locality properties of object keys, the critical properties to many applications, more specifically, those that require range searching. To preserve a key order while keeping loads balanced, Ganesan, Bawa, and Garcia-Molina proposed a load-balancing algorithm that supports both object's key insertion and deletion with a guaranteed max-min load ratio, the imbalance ratio, of 4.237 using constant amortized costs. Nonetheless, the algorithm is not straightforward to implement in real networks because of its recursiveness. The algorithm mostly uses local operations with global max-min load information. In this work, we present a simple nonrecursive algorithm using essentially the same primitive operations as in Ganesan et al.'s work. For insertions and deletions, our algorithm guarantees a proven constant imbalance ratio of 7.464 with constant amortized costs. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 66(3), 235-249 2015 [ABSTRACT FROM AUTHOR]

Heterogeneous networks improve the spectrum efficiency and coverage of wireless communication networks by deploying low-power nodes on top of the conventional network nodes. In this paper, we consider a heterogeneous cellular network with multiple low-power relay nodes (RN) deployed in each cell using in-band wireless backhaul link between the RN and the base station (BS). The RNs work cooperatively with the BSs on the downlink communication towards the user equipments. Due to the disparity between the transmit powers of the BSs and the RNs, mobile association schemes developed for the conventional homogeneous networks may lead to a highly unbalanced traffic load distribution with most of the traffic being concentrated on the BSs. In this paper, we propose a new mobile association framework for the heterogeneous wireless networks with node cooperation. The proposed framework aims to maximize the network capacity and balance the traffic load among the network nodes. A pseudo-optimal solution is obtained for the proposed mobile association framework using a centralized gradient-descent algorithm. To enable online implementation, we further introduce a distributed algorithm using a pricing mechanism. Numerical results show that a prominent improvement in network capacity can be achieved by the proposed load balancing-based mobile association scheme compared with the conventional counterpart. Moreover, compared with the pseudo-optimal solution, the proposed pricing-based distributed algorithm only suffers a small loss in network capacity and thus can be considered as an efficient real-time implementation alternative. [ABSTRACT FROM AUTHOR]

In large scale agent-based simulations, memory and computational power requirements can increase dramatically because of high numbers of agents and interactions. To be able to simulate millions of agents, distributing the simulator on a computer network is promising, but raises some issues like: agents allocation and load-balancing between machines. In this paper, we study the best ways to automatically balance the loads between machines in large scale situations. We study the performance of two different applications with two different distribution approaches, and we show in our experimental results that some applications can automatically adapt the loads between machines and get alone a high performance in large scale simulations with one distribution approach than the other. [ABSTRACT FROM AUTHOR]

We present a new overlay, called the Deterministic Decentralized tree ( $$D^2$$ -tree). The $$D^2$$ -tree compares favorably to other overlays for the following reasons: (a) it provides matching and better complexities, which are deterministic for the supported operations; (b) the management of nodes (peers) and elements are completely decoupled from each other; and (c) an efficient deterministic load-balancing mechanism is presented for the uniform distribution of elements into nodes, while at the same time probabilistic optimal bounds are provided for the congestion of operations at the nodes. The load-balancing scheme of elements into nodes is deterministic and general enough to be applied to other hierarchical tree-based overlays. This load-balancing mechanism is based on an innovative lazy weight-balancing mechanism, which is interesting in its own right. [ABSTRACT FROM AUTHOR]

Software defined networking (SDN) provides great flexibility by decoupling the control and the data planes, allowing for the implementation of new and innovative network control plane experiments. Presently, the reference implementation for SDN architecture is reliant upon a single controller to push flow rules to all SDN-enabled switches in the network, creating a performance bottleneck and single-point of failure in large networks. To provide a scalable yet efficient solution to distributed SDN network management, we propose FlowBroker, a hierarchical brokering agent layer which manages and coordinates among distributed SDN controllers, where each controller is charged with the flow-rule maintenance of the switches in its managed domain. This paper proposes the FlowBroker architecture as a collaborative multi-domain approach to load balancing and network performance enhancement in software-defined networks. Moreover, we introduce distributed machine learning agents to allow controllers to evaluate which brokers are more advantageous than others, from a performance-based reputation perspective. Simulation results show that the FlowBroker architecture, with broker-based collaborative load-balancing and controller-based distributed reputation, can significantly increase the network performance of a multi-domain software-defined network. FlowBroker yields significant reductions in traffic loss, end-to-end delay and maximum link utilization when cooperative brokering and reputation are utilized. [ABSTRACT FROM AUTHOR]

This paper proposes load-balancing algorithm on the basis of the Extended Dijkstra's shortest path algorithm for Software Defined Networking (SDN). The Extended Dijkstra's algorithm considers not only the edge weights, but also the node weights to find the nearest server for a requesting client. The proposed algorithm also considers the link load in order to avoid congestion. We use Pyretic to implement the proposed algorithm and compare it with related ones under the Abilene network topology with the Mininet emulation tool. As shown by the comparisons, the proposed algorithm outperforms the others in term of the network end-to-end latency, and throughput. [ABSTRACT FROM AUTHOR]

One of the key challenges for research in wireless sensor networks is the development of routing protocols that provide application-specific service guarantees. This paper presents a new cluster-based Route Optimisation and Load-balancing protocol, called ROL, that uses various Quality of Service (QoS) metrics to meet application requirements. ROL combines several application requirements, specifically it attempts to provide an inclusive solution to prolong network life, provide timely message delivery and improve network robustness. It uses a combination of routing metrics that can be configured according to the priorities of user-level applications to improve overall network performance. To this end, an optimisation tool for balancing the communication resources for the constraints and priorities of user applications has been developed and Nutrient-flow-based Distributed Clustering (NDC), an algorithm for load balancing is proposed. NDC works seamlessly with any clustering algorithm to equalise, as far as possible, the diameter and the membership of clusters. This paper presents simulation results to show that ROL/NDC gives a higher network lifetime than other similar schemes, such Mires++. In simulation, ROL/NDC maintains a maximum of 7% variation from the optimal cluster population, reduces the total number of set-up messages by up to 60%, reduces the end-to-end delay by up to 56%, and enhances the data delivery ratio by up to 0.98% compared to Mires++. [ABSTRACT FROM AUTHOR]

Highlights: [•] We parallelize a key kernel on the critical path of multishift QR algorithms. [•] We develop a fine-grained pipelined bulge-chasing kernel for multicore processors. [•] Empirical optimization adapts the load-balance parameters to the target system. [ABSTRACT FROM AUTHOR]

Today's mobile terminals have several access network interfaces. New protocols have been proposed during the last few years to enable the concurrent use of multiple access paths for data transmission. In practice, the use of different access technologies is subject to different interconnection costs, and mobile users have preferences on interfaces jointly depending on performance and cost factors. There is therefore an interest in defining “light” multipath communication policies that are less expensive than greedy unconstrained ones such as with basic multipath TCP (MP-TCP) and that are strategically acceptable assuming a selfish endpoint behavior. With this goal, we analyze the performance-cost trade-off of multi-homed end-to-end communications from a strategic standpoint. We model the communication between multi-homed terminals as a specific non-cooperative game to achieve performance-cost decision frontiers. The resulting potential game always allows selecting multiple equilibria, leading to a strategic load-balancing distribution over the available interfaces, possibly constraining their use with respect to basic MP-TCP. By simulation of a realistic three-interface scenario, we show how the achievable performance is bound by the interconnection cost; we show that we can halve the interconnection cost with respect to basic (greedy) MP-TCP while offering double throughputs with respect to single-path TCP. Moreover, we evaluate the compromise between keeping or relaxing strategic constraints in a coordinated MP-TCP context. [ABSTRACT FROM PUBLISHER]

Advancements in operating system virtualization and storage virtualization technologies have enabled the effective consolidation of heterogeneous applications in a shared cloud infrastructure. Research challenges which are novel arising from this new shared environment include load balancing, resource isolation, workload estimation, live migration, machine replication, and an emergent need of automation to handle large scale operations with minimal manual intervention. Databases are at the core of most applications that are deployed in the cloud, database management systems (DBMSs) represent a very important technology component that needs to be virtualized in order to realize the benefits of virtualization from autonomic management of data-intensive applications in large scale data-centers. The goal of this paper is to survey the techniques used in providing elasticity in virtual machine systems, shared storage systems and survey on database research on multitenant architectures and elasticity primitives. Studying Database as a Service advances, together with study of related topics in OS and storage-level virtualization, as they are central for anyone that wants to operate in this area. [ABSTRACT FROM AUTHOR]

There has been a great deal of interest recently in load-balancing switches due to their simple architecture and high forwarding bandwidth. Nevertheless, the mis-sequencing problem of the original load-balancing switch hinders the performance of underlying TCP applications. Several load-balancing switch designs have been proposed to address this mis-sequencing issue. They solve this mis-sequencing problem at the cost of either algorithmic complexity or special hardware requirements. In this paper, we address the mis-sequencing problem by introducing a three-stage load-balancing switch architecture enhanced with an output load-balancing mechanism. This three-stage load-balancing switch achieves a high forwarding capacity while preserving the order of packets without the need of costly online scheduling algorithms. Theoretical analyses and simulation results show that this three-stage load-balancing switch provides a transmission delay that is upper-bounded by that of an output-queued switch plus a constant that depends only on the number of input/output ports, indicating the same forwarding capacity as an output-queued switch. [ABSTRACT FROM AUTHOR]

Abstract: Energy consumption has been the focus of many studies on Wireless Sensor Networks (WSN). It is well recognized that energy is a strictly limited resource in WSNs. This limitation constrains the operation of the sensor nodes and somehow compromises the long term network performance as well as network activities. Indeed, the purpose of all application scenarios is to have sensor nodes deployed, unattended, for several months or years. This paper presents the lifetime maximization problem in “many-to-one” and “mostly-off” wireless sensor networks. In such network pattern, all sensor nodes generate and send packets to a single sink via multi-hop transmissions. We noticed, in our previous experimental studies, that since the entire sensor data has to be forwarded to a base station via multi-hop routing, the traffic pattern is highly non-uniform, putting a high burden on the sensor nodes close to the base station. In this paper, we propose some strategies that balance the energy consumption of these nodes and ensure maximum network lifetime by balancing the traffic load as equally as possible. First, we formalize the network lifetime maximization problem then we derive an optimal load balancing solution. Subsequently, we propose a heuristic to approximate the optimal solution and we compare both optimal and heuristic solutions with most common strategies such as shortest-path and equiproportional routing. We conclude that through the results of this work, combining load balancing with transmission power control outperforms the traditional routing schemes in terms of network lifetime maximization. [Copyright &y& Elsevier]

Agent-based simulation models are an increasingly popular tool for research and management in many fields. In executing such simulations “speed” is one of the most general and important issues because of the size and complexity of simulations. But another important issue is the effectiveness of the solution, which consists of how easily usable and portable the solutions are for the users, i.e. the programmers of the distributed simulation. Our study, then, is aimed at efficient and effective distribute simulations by adopting a framework-level approach, with our design and implementation of a framework, D-Mason, which is a parallel version of the Mason library for writing and running simulations of agent-based simulation models. In particular, besides the efficiency due to workload distribution with small overhead, D-Mason at a framework level proves itself effective since it enables the scientists that use the framework (domain expert but with limited knowledge of distributed programming) only minimally aware of the fact that the simulation is running on a distributed environment. Then, we present tests that compare D-Mason against Mason in order to assess the improved scalability and D-Mason capability to exploit heterogeneous distributed hardware. Our tests also show that several massive simulations that are impossible to execute on Mason (e.g. because of CPU and/or memory requirements) can be easily performed using D-Mason. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we address the issue of joint routing, channel re-assignment and rate allocation in multi-radio multi-channel Wireless Mesh Networks (WMNs) with the goal of optimizing the performance of the current set of flows in the WMN. The objective is to balance the instantaneous traffic in the network at the flow level, optimize link-channel assignment and allocate flow rates to achieve proportional fairness given the current traffic and network constraints, including the topology, interference characteristics, number of available channels and radios. Unlike prior work, we do not assume a priori knowledge of traffic, and instead take into account the instantaneous traffic conditions to optimize performance at the flow level, taking both throughput and fairness into account. In this work we analyze the problem and, due to its hardness, propose a fast heuristic algorithm (JRCAR) to solve it. We evaluate this algorithm through numerical experiments, including comparisons against optimal solutions. In addition, we show that JRCAR can be used in a highly responsive system in practical scenarios with time-varying traffic conditions. We implement such a system under the ns-3 simulator, where the simulation results obtained corroborate the behavior observed in the numerical experiments and show that JRCAR is effective in dynamic and practical conditions. [Copyright &y& Elsevier]

Radio Frequency Identification (RFID) technology; a convenient and flexible technology which is well suited for fully automated systems, is directing human lifestyle towards automation and reality. Integrating RFID into attendance management systems makes the tasks of both users and administrators easy, smart, convenient, and practical. Earlier implementations of RFID-based attendance systems involve different approaches and facilities. Different intertwined characteristics (i.e., scalability, and automation) are suggested in evaluating the performance of these systems. The coverage of these characteristics appears to be adequate in achieving a good systems implementation. Some of the existing systems present high performance; however, these systems still have gaps in some of the suggested characteristics. In order to mind these gaps, a scalable RFID-based attendance system with an intelligent scheduling technique; called Intelligent and fully Automated Attendance System (IAAS), has been designed and implemented. Finally, the performance of IAAS has been evaluated through a comparison with existing attendance systems. [ABSTRACT FROM AUTHOR]

Wireless mesh networks (WMNs) provide high-bandwidth wireless access, which makes it capable for multimedia services. A user in a WMN may be covered by multiple APs, while it should be associated with only one to access the Internet. Conventional IEEE 802.11 user-AP association mechanism for WLANs employs signal strength as the sole metric. However, this may lead to network congestion and performance degradation in multi-hop networks such as WMNs, especially for multimedia services that require a large bandwidth and a low latency. Thus AP association in WMNs becomes an important research issue. In this paper we propose a novel AP association approach LBAA, taking AP's load-balancing, WMN's multi-hop characteristic, and user's RSSI into consideration. We first propose a centralized algorithm and then extend it to a distributed one, with the latter one more practical and convenient for deployment. Network throughput and max-min user fairness are improved by LBAA. Performance evaluation demonstrating the benefits of our approach is given through a series of experiments in terms of collision probability, access bandwidth, end-to-end throughput, and average RSSI. [ABSTRACT FROM AUTHOR]

Box intersection checking is a common task used in many large-scale simulations. Traditional methods cannot provide fast box intersection checking with large-scale datasets. This article presents a parallel algorithm to perform Pairwise Box Intersection checking on Graphics processing units (PBIG). The PBIG algorithm consists of three phases: planning, mapping and checking. The planning phase partitions the space into small cells, the sizes of which are determined to optimize performance. The mapping phase maps the boxes into the cells. The checking phase examines the box intersections in the same cell. Several performance optimizations, including load-balancing, output data compression/encoding, and pipelined execution, are presented for the PBIG algorithm. The experimental results show that the PBIG algorithm can process large-scale datasets and outperforms three well-performing algorithms. [ABSTRACT FROM AUTHOR]

Nowadays, many geocomputations are benefiting from parallel computing technologies. As a category of data and computationally intensive problems, Digital Terrain Analysis (DTA) can be improved by parallelization based on data parallelism. Load-balancing is one of the factors impacting the performance of a parallel DTA algorithm. In this article, we propose a theoretical approach that can schedule tasks for complex DTA parallel algorithms with respect to load-balancing among processors. First, we analyse the reason why the newly emerged theory of spatial computational domain is not suitable for complex DTA algorithms. Then, (1) by using the theory of cellular automata, a complex DTA algorithm can be modelled and thus decomposed into multiple simplex transitions; (2) by developing a trans-function for each simplex transition, load-balancing can be achieved for every transition, respectively; and (3) by solving the data reloading and results passing issues, all the simplex transitions can be linked back to the complex algorithm. The highlight of our approach is that the generated task scheduling solution always keeps adjusting itself as the algorithm proceeds one transition by another. This highlight also leads to a better load-balancing effect, which has been verified by a series of comparative experiments. In the experimental case, the parallel computing time using our approach becomes shorter than the one using the conventional approach. The decreasing ratio is 13.4%. [ABSTRACT FROM AUTHOR]

Task scheduling is one of the core issues of grid computing, scheduling strategy will directly affect the performance of grid system. Based on analysis and comparison to the existing heuristic scheduling algorithm, for the task scheduling problem of the computing grid which with the high-throughput application, proposed a algorithm based on comprehensive consideration of resources performance metrics and task node needs, the algorithm based on task priority and load-balancing task scheduling algorithm. With a simulation experiment, compare with the traditional three aspects of Min-min algorithm Max-min algorithm and Sufferage comparison algorithm in the task completion time and system resource utilization. The simulation results show that this algorithm not only makes the overall task completion time are reduced, but also improve the utilization of system resources,so it proves that the algorithm is effective, and more suitable for applications in high-throughput scheduling. [ABSTRACT FROM AUTHOR]

This paper presents flow-aware routing protocol (FARP), a new routing strategy designed to improve load balancing and scalability in mobile ad hoc networks. FARP is a hop-by-hop routing protocol, which introduces a flow-aware route discovery strategy to reduce the number of control overheads propagating through the network and distributes the flow of data through least congested nodes to balance the network traffic. FARP was implemented in GloMoSim and compared with AODV. To investigate the load distribution capability of FARP new performance metrics were introduced to measure the data packet flow distribution capability of the each routing protocol. The simulation results obtained illustrate that FARP achieves high levels of throughput, reduces the level of control overheads during route discovery and distributes the network load more evenly between nodes when compared to AODV. This paper also describes a number of alternative strategies and improvements for the FARP.

Abstract: Distributing the workload upon all available Processing Units (PUs) of a high-performance heterogeneous platform (e.g., PCs composed by CPU–GPUs) is a challenging task, since the execution cost of a task on distinct PUs is non-deterministic and affected by parameters not known a priori. This paper presents Sm@rtConfig, a context-aware runtime and tuning system based on a compromise between reducing the execution time of engineering applications and the cost of tasks'' scheduling on CPU–GPUs'' platforms. Using Model-Driven Engineering and Aspect Oriented Software Development, a high-level specification and implementation for Sm@rtConfig has been created, aiming at improving modularization and reuse in different applications. As case study, the simulation subsystem of a CFD application has been developed using the proposed approach. These system''s tasks were designed considering only their functional concerns, whereas scheduling and other non-functional concerns are handled by Sm@rtConfig aspects, improving tasks modularity. Although Sm@rtConfig supports multiple PUs, in this case study, these tasks have been scheduled to execute on an platform composed by one CPU and one GPU. Experimental results show an overall performance gain of 21.77% in comparison to the static assignment of all tasks only to the GPU. [Copyright &y& Elsevier]

Abstract: Thanks to advances in the computing capabilities and added functionalities of modern mobile devices, creating and consuming digital media on the move has never been so easy and popular. Most of the DTN routing protocols proposed in the literature to enable content sharing have been exploiting users’ mobility patterns, in order to maximise the delivery probability, while minimising the overall network overhead (e.g., number of message replicas in the system, messages’ path length). Common to all these protocols has been the assumption that devices are willing to participate in the content distribution network; however, because of battery constraints, participation cannot be taken for granted, especially if the very same subset of devices are continuously selected as content carriers, simply because of their mobility properties. Indeed, we demonstrate that state-of-the-art DTN routing protocols distribute load in a highly unfair manner, with detrimental effects on delivery once the assumption of unconditional participation is lifted. To overcome this limitation, we propose a load-balancing mechanism whereby nodes maintain local estimates of network workload, and use them to direct traffic towards the least loaded portion of the network. We implement the mechanism on top of a source-based DTN routing protocol, and demonstrate, by means of simulation using a variety of real mobility traces, that high delivery is now achieved without compromising fairness. [Copyright &y& Elsevier]

In this paper, we revisit the problem of load-balancing structured peer-to-peer systems with on-line protocols. Load-balancing is of major significance for large-scale decentralized networks in terms of enhanced scalability and performance. The main incentives behind balancing schemes are under-utilization of bandwidth and computer resources. Therefore, our methods focus mainly on task-skew. Specifically, we address the problem with on-line protocols on the basis of migration and enhanced availability. In particular, the cornerstones of our methods are the notions of virtual nodes, replication and Multiple realities, combined altogether with allocation techniques based on balls-in-bins games. The rationale of our dynamic protocol to depend exclusively on peer load distribution preserves intact the structural properties and search efficiency of the overlay used as an indexing infrastructure, while preserving the semantic information of the data (e.g., range partitioned network). We also propose an effective load-aware mechanism to facilitate robust operations that counteract against contingent churn failures. Finally, our work is complemented with extensive experiments using both real and synthetic data sets. [ABSTRACT FROM AUTHOR]

Publish/subscribe systems have emerged in recent years as a promising paradigm for offering various popular notification services. In this context, many XML filtering systems have been proposed to efficiently identify XML data that matches user interests expressed as queries in an XML query language like XPath. However, in order to offer XML filtering functionality on an Internet-scale, we need to deploy such a service in a distributed environment, avoiding bottlenecks that can deteriorate performance. In this work, we design and implement FoXtrot, a system for filtering XML data that combines the strengths of automata for efficient filtering and distributed hash tables for building a fully distributed system. Apart from structural-matching, performed using automata, we also discuss different methods for evaluating value-based predicates. We perform an extensive experimental evaluation of our system, FoXtrot, on a local cluster and on the PlanetLab network and demonstrate that it can index millions of user queries, achieving a high indexing and filtering throughput. At the same time, FoXtrot exhibits very good load-balancing properties and improves its performance as we increase the size of the network. [ABSTRACT FROM AUTHOR]