Game of energy consumption balancing in heterogeneous sensor networks

In a multi‐hop sensor network, sensors largely rely on other nodes as a traffic relay to communicate with targets that are not reachable by one hop. Depending on the topology and position of nodes, some sensors receive more relaying traffic and lose their energy faster. Such imbalanced energy consumption may lead to server problems like network partitioning. In this paper, we study the problem of energy consumption balancing (ECB) in heterogeneous sensor networks by assuming general any‐to‐any traffic pattern. We consider both factors of transmission power and forwarding load in measuring energy consumption. To find a solution, we formulate the problem as a strategic network formation game with a new utility function. We show that this game is guaranteed to converge to strongly connected topologies which have better ECB and bounded inefficiency. We propose a localized algorithm in which every node knows only about its k‐hop neighbourhood. Through simulations on uniform and clustered networks with various densities, we show that the performance of our algorithm is comparable with global and centralized algorithms. Copyright © 2015 John Wiley & Sons, Ltd.     

The stable paths problem and interdomain routing

Dynamic routing protocols such as RIP and OSPF essentially implement distributed algorithms for solving the shortest paths problem. The border gateway protocol (BGP) is currently the only interdomain routing protocol deployed in the Internet. BGP does not solve a shortest paths problem since any interdomain protocol is required to allow policy-based metrics to override distance-based metrics and enable autonomous systems to independently define their routing policies with little or no global coordination. It is then natural to ask if BGP can be viewed as a distributed algorithm for solving some fundamental problem. We introduce the stable paths problem and show that BGP can be viewed as a distributed algorithm for solving this problem. Unlike a shortest path tree, such a solution does not represent a global optimum, but rather an equilibrium point in which each node is assigned its local optimum. We study the stable paths problem using a derived structure called a dispute wheel, representing conflicting routing policies at various nodes. We show that if no dispute wheel can be constructed, then there exists a unique solution for the stable paths problem. We define the simple path vector protocol (SPVP), a distributed algorithm for solving the stable paths problem. SPVP is intended to capture the dynamic behavior of BGP at an abstract level. If SPVP converges, then the resulting state corresponds to a stable paths solution. If there is no solution, then SPVP always diverges. In fact, SPVP can even diverge when a solution exists. We show that SPVP will converge to the unique solution of an instance of the stable paths problem if no dispute wheel exists     

无线传感器网络下线性支持向量机分布式协同训练方法研究

针对无线传感器网络中分散在各节点上的训练数据传输到数据融合中心集中训练支持向量机(Support Vector Machine, SVM)时存在的高通信代价和高能量消耗问题,该文研究了仅依靠相邻节点间的相互协作,在网内分布式协同训练线性SVM的方法。首先,在各节点分类器决策变量与集中式分类器决策变量相一致的约束下,对集中式SVM训练问题进行等价分解,然后利用增广拉格朗日乘子法,对分解后的SVM问题进行求解和推导,进而提出基于全局平均一致性的线性SVM分布式训练算法(Average Consensus based Distributed Supported Vector Machine, AC-DSVM);为了降低AC-DSVM算法中全局平均一致性的通信开销,利用相邻节点间的局部平均一致性近似全局平均一致性,提出基于一次全局平均一致性的线性SVM分布式训练算法(Once Average Consensus based Distributed Supported Vector Machine, 1-AC-DSVM)。仿真实验结果表明,与已有算法相比,AC-DSVM算法的迭代次数和数据传输量略高,但其能够完全收敛到集中式训练结果;1-AC-DSVM算法具有较好的收敛性,而且在收敛速度和数据传输量上也表现出显著优势。     

Effect of Selfish Node Behavior on Efficient Topology Design

The problem of topology control is to assign per-node transmission power such that the resulting topology is energy-efficient and satisfies certain global properties such as connectivity. The conventional approach to achieve these objectives is based on the fundamental assumption that nodes are socially responsible. We examine the following question: if nodes behave in a selfish manner, how does it impact the overall connectivity and energy consumption in the resulting topologies? We pose the above problem as a non-cooperative game and use game-theoretic analysis to address it. We study Nash equilibrium properties of the topology control game and evaluate the efficiency of the induced topology when nodes employ a greedy best response algorithm. We show that even when the nodes have complete information about the network, the steady state topologies are suboptimal. We propose a modified algorithm based on a better response dynamic and show that this algorithm is guaranteed to converge to energy-efficient and connected topologies. Moreover, the node transmit power levels are more evenly distributed and the network performance is comparable to that obtained from centralized algorithms.     

Maximum lifetime broadcast communications in cooperative multihop wireless ad hoc networks: Centralized and distributed approaches

We investigate the problem of broadcast routing in energy constrained stationary wireless ad hoc networks with an aim to maximizing the network lifetime measured as the number of successive broadcast sessions that can be supported. We propose an energy-aware spanning tree construction scheme supporting a broadcast request, considering three different signal transmission schemes in the physical layer: (a) point-to-point, (b) point-to-multipoint, and (c) multipoint-to-point. First we present a centralized algorithm that requires global topology information. Next, we extend this to design an approximate distributed algorithm, assuming the availability of k-hop neighborhood information at each node, with k as a parameter. We prove that the centralized scheme has time complexity polynomial in the number of nodes and the distributed scheme has a message complexity that is linear in the number of nodes. Results of numerical experiments demonstrate significant improvement in network lifetime following our centralized scheme compared to existing prominent non-cooperative broadcasting schemes proposed to solve the same lifetime maximization problem in wireless ad hoc networks. Due to lack of global topology information, the distributed solution does not produce as much advantage as the centralized solution. However, we demonstrate that with increasing value of k, the performance of the distributed scheme also improves significantly.     

The n-Hop Multilateration Primitive for Node Localization Problems

The recent advances in MEMS, embedded systems and wireless communication technologies are making the realization and deployment of networked wireless microsensors a tangible task. In this paper we study node localization, a component technology that would enhance the effectiveness and capabilities of this new class of networks. The n-hop multilateration primitive presented here, enables ad-hoc deployed sensor nodes to accurately estimate their locations by using known beacon locations that are several hops away and distance measurements to neighboring nodes. To prevent error accumulation in the network, node locations are computed by setting up and solving a global non-linear optimization problem. The solution is presented in two computation models, centralized and a fully distributed approximation of the centralized model. Our simulation results show that using the fully distributed model, resource constrained sensor nodes can collectively solve a large non-linear optimization problem that none of the nodes can solve individually. This approach results in significant savings in computation and communication, that allows fine-grained localization to run on a low cost sensor node we have developed.     

Efficient Cache Placement in Multi-Hop Wireless Networks

In this paper, we address the problem of efficient cache placement in multi-hop wireless networks. We consider a network comprising a server with an interface to the wired network, and other nodes requiring access to the information stored at the server. In order to reduce access latency in such a communication environment, an effective strategy is caching the server information at some of the nodes distributed across the network. Caching, however, can imply a considerable overhead cost; for instance, disseminating information incurs additional energy as well as bandwidth burden. Since wireless systems are plagued by scarcity of available energy and bandwidth, we need to design caching strategies that optimally trade-off between overhead cost and access latency. We pose our problem as an integer linear program. We show that this problem is the same as a special case of the connected facility location problem, which is known to be NP-hard. We devise a polynomial time algorithm which provides a suboptimal solution. The proposed algorithm applies to any arbitrary network topology and can be implemented in a distributed and asynchronous manner. In the case of a tree topology, our algorithm gives the optimal solution. In the case of an arbitrary topology, it finds a feasible solution with an objective function value within a factor of 6 of the optimal value. This performance is very close to the best approximate solution known today, which is obtained in a centralized manner. We compare the performance of our algorithm against three candidate cache placement schemes, and show via extensive simulation that our algorithm consistently outperforms these alternative schemes.     

Joint scheduling and power control supporting multicasting in wireless ad hoc networks

This paper addresses the problem of power control in a multihop wireless network supporting multicast traffic. We face the problem of forwarding packet traffic to multicast group members while meeting constraints on the signal-to-interference-plus-noise ratio (SINR) at the intended receivers. First, we present a distributed algorithm which, given the set of multicast senders and their corresponding receivers, provides an optimal solution when it exists, which minimizes the total transmit power. When no optimal solution can be found for the given set of multicast senders and receivers, we introduce a distributed, joint scheduling and power control algorithm which eliminates the weak connections and tries to maximize the number of successful multicast transmissions. The algorithm allows the other senders to solve the power control problem and minimize the total transmit power. We show that our distributed algorithm converges to the optimal solution when it exists, and performs close to centralized, heuristic algorithms that have been proposed to address the joint scheduling and power control problem.     

集中与分布:协同虚拟网络映射

结合传统集中式和分布式两类算法各自的特性,提出了协同虚拟网络映射算法。该算法保留了集中式算法中拥有全局视野的中心控制实体,负责总体控制和关键决策,同时将具体映射方案的计算过程交给有限的底层网络子集实现;唯一的中心控制实体与多个底层节点相互配合协作,共同完成虚拟网络映射的整个过程。该算法继承了集中式和分布式算法各自的优势,有效弥补了二者的缺陷,初步的仿真试验也证明了其可行性和有效性。     

基于进化优化的移动感知节点部署算法

 移动传感器网络中节点部署优化直接影响到网络的能量消耗、对目标区域监控的性能及整个网络的生命周期.本文从网络覆盖和能量消耗两个方面,采用多目标优化对节点部署问题建模,并从集中式角度给出了节点部署问题的遗传算法求解过程.针对一类初始中心部署模型进行实验验证,并和基于向量的算法(VEC)、基于维诺图的算法(VOR)及基于边界扩张虚拟力算法(BEVF)进行性能对比,证明了该算法在大多数情况下可使传感器网络对目标区域的覆盖率最大化,同时保证了网络的连通和网络能耗最小,进而延长了网络的生命周期.     

TDMA scheduling algorithms for wireless sensor networks

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.     

Cooperative multihop broadcast for wireless networks

We address the minimum-energy broadcast problem under the assumption that nodes beyond the nominal range of a transmitter can collect the energy of unreliably received overheard signals. As a message is forwarded through the network, a node will have multiple opportunities to reliably receive the message by collecting energy during each retransmission. We refer to this cooperative strategy as accumulative broadcast. We seek to employ accumulative broadcast in a large scale loosely synchronized, low-power network. Therefore, we focus on distributed network layer approaches for accumulative broadcast in which loosely synchronized nodes use only local information. To further simplify the system architecture, we assume that nodes forward only reliably decoded messages. Under these assumptions, we formulate the minimum-energy accumulative broadcast problem. We present a solution employing two subproblems. First, we identify the ordering in which nodes should transmit. Second, we determine the optimum power levels for that ordering. While the second subproblem can be solved by means of linear programming, the ordering subproblem is found to be NP-complete. We devise a heuristic algorithm to find a good ordering. Simulation results show the performance of the algorithm to be close to optimum and a significant improvement over the well known BIP algorithm for constructing energy-efficient broadcast trees. We then formulate a distributed version of the accumulative broadcast algorithm that uses only local information at the nodes and has performance close to its centralized counterpart.     

LIS: Localization based on an intelligent distributed fuzzy system applied to a WSN

The localization of the sensor nodes is a fundamental problem in wireless sensor networks. There are a lot of different kinds of solutions in the literature. Some of them use external devices like GPS, while others use special hardware or implicit parameters in wireless communications.In applications like wildlife localization in a natural environment, where the power available and the weight are big restrictions, the use of hungry energy devices like GPS or hardware that add extra weight like mobile directional antenna is not a good solution.Due to these reasons it would be better to use the localization’s implicit characteristics in communications, such as connectivity, number of hops or RSSI. The measurement related to these parameters are currently integrated in most radio devices. These measurement techniques are based on the beacons’ transmissions between the devices.In the current study, a novel tracking distributed method, called LIS, for localization of the sensor nodes using moving devices in a network of static nodes, which have no additional hardware requirements is proposed.The position is obtained with the combination of two algorithms; one based on a local node using a fuzzy system to obtain a partial solution and the other based on a centralized method which merges all the partial solutions. The centralized algorithm is based on the calculation of the centroid of the partial solutions.Advantages of using fuzzy system versus the classical Centroid Localization (CL) algorithm without fuzzy preprocessing are compared with an ad hoc simulator made for testing localization algorithms.With this simulator, it is demonstrated that the proposed method obtains less localization errors and better accuracy than the centroid algorithm.     

An Algorithm for Evaluation of Throughput in Multihop Packet Radio Networks with Complex Topologies

The problem of analyzing the thoughput of packet radio networks with realistic topologies is considered. We present an algorithm for the solution of this problem and show that both the memory requirements and running time of this algorithm in practice grow polynomially with the size of the problem. Although in theory both can grow exponentially in the worst case, we offer computational experience with the procedure and show that for realistic topologies where connectivity is related to distance, the rate of growth is quadratic in the number of links. Even for regular grids, which are pathological in their symmetry, the rate of growth is only cubic in the number of links. We thus conclude that the procedure is effective for realistic topologies with up to several hundred nodes.     

Simultaneous area and delay minimum K-LUT mapping for K-exact networks

We address the technology mapping problem for lookup table FPGAs. The area minimization problem, for mapping K-bounded networks, consisting of nodes with at most K inputs, using K-input lookup tables, is known to be NP-complete for K 5. The complexity was unknown for K = 2, 3, and 4. The corresponding delay minimization problem (under the constant delay model) was solved in polynomial time by the flow-map algorithm, for arbitrary values of K. We study the class of K-bounded networks, where all nodes have exactly K inputs. We call such networks K-exact. We give a characterization of mapping solutions for such networks. This leads to a polynomial time algorithm for computing the simultaneous area and delay minimum mapping for such networks using K-input lookup tables. We also show that the flow-map algorithm computes the same mapping solution as our algorithm. We then show that for K = 2 the mapping solution for a 2-bounded network, minimizing the area and delay simultaneously, can be easily obtained from that of a 2-exact network derived from it by eliminating single input nodes. Thus the area minimization problem for 2-input lookup tables can be solved in polynomial time, resolving an open problem.     

WLAN中合作式功率控制算法研究

在WLAN中,延迟有限,网络整体消耗能量最小化的功率控制算法研究较少。对于该问题进行建模分析,通过理论推导,将该非凸优化问题转化成广义几何规划问题。经过分析,将问题近似为线性规划,并给出全局优化算法。对于WLAN中,多个无线接入设备在一定传输时间内的信道情况进行预测,给出延迟有限能量最小化的集中式在线算法。实验结果显示,采用提出的信道预测方法,在线算法的计算结果与集中式算法结果较为接近。     

Distributed algorithms for multicast path setup in data networks

Establishing a multicast tree in a point-to-point network of switch nodes, such as a wide-area asynchronous transfer mode (ATM) network, can be modeled as the NP-complete Steiner problem in networks. In this paper, we introduce and evaluate two distributed algorithms for finding multicast trees in point-to-point data networks. These algorithms are based on the centralized Steiner heuristics, the shortest path heuristic (SPH) and the Kruskal-based shortest path heuristic (K-SPH), and have the advantage that only the multicast members and nodes in the neighborhood of the multicast tree need to participate in the execution of the algorithm. We compare our algorithms by simulation against a baseline algorithm, the pruned minimum spanning-tree heuristic that is the basis of many previously published algorithms for finding multicast trees. Our results show that the competitiveness (the ratio of the sum of the heuristic tree's edge weights to that of the best solution found) of both of our algorithms was, on the average, 25% better in comparison to that of the pruned spanning-tree approach. In addition, the competitiveness of our algorithms was, in almost all cases, within 10% of the best solution found by any of the Steiner heuristics considered, including both centralized and distributed algorithms. Limiting the execution of the algorithm to a subset of the nodes in the network results in an increase in convergence time over the pruned spanning-tree approach, but this overhead can be reduced by careful implementation     

Distributed dynamic fault-tolerant channel allocation for cellularnetworks

Efficient allocation of communication channels is critical for the performance of cellular systems. The centralized channel allocation algorithms proposed in literature are neither robust nor scalable. Several of these algorithms are unable to dynamically adjust to spatial and temporal fluctuations in channel demand (load). We present a distributed dynamic channel allocation (DCA) algorithm in which heavily loaded regions acquire a large number of communication channels, while their lightly loaded neighbors get assigned fewer channels. As the spatial distribution of channel demand changes with time, the spatial distribution of allocated channels adjusts accordingly. The algorithm described in this paper requires minimal involvement of the mobile nodes, thus conserving their limited energy supply. The algorithm is proved to be deadlock free, starvation free, and fair. It prevents cochannel interference and can tolerate the failure of mobile as well as static nodes without any significant degradation in service. Simulation experiments demonstrate that the performance of the proposed distributed dynamic algorithm is comparable to, and for some metrics, better than that of efficient centralized dynamic algorithms where the central switch has complete and latest information about channel availability. The major advantages of the proposed algorithm over its dynamic centralized counterparts are its scalability, flexibility, and low computation and communication overheads     

Traffic engineering in a multipoint-to-point network

The need to guarantee quality-of-service (QoS) to multimedia applications leads to a tight integration between the routing and forwarding functions in the Internet. multiprotocol label switching tries to provide a global solution for this integration. In this context, multipoint-to-point (m2p) networks appear as a key architecture since they provide a cheaper way to connect edge nodes than point-to-point connections. M2p networks have been mainly studied for their load balancing ability. In this paper, we go a step further: we propose and evaluate a traffic management scheme that provides deterministic QoS guarantees for multimedia sources in an m2p network. We first derive an accurate upper bound on the end-to-end delay in an m2p architecture based on the concept of additivity. Broadly speaking, an m2p network is additive if the maximum end-to-end delay is equal to the sum of local maximum delays. We then introduce two admission control algorithms for additive networks: a centralized algorithm and a distributed algorithm and discuss their complexity and their scalability     

Minimizing broadcast latency and redundancy in asynchronous wireless sensor networks

Asynchronous duty cycle Medium Access Control (MAC) protocols do not require global synchronization because nodes determine their wake-up schedule independently. As a result, these MACs have superior performance to those that employ synchronous duty-cycles in terms of energy expenditure, and advantageously, they are simple to implement. A key limitation is that they do not support efficient broadcast. A node needs to transmit a broadcast packet multiple times via unicast because only a subset of its neighbors may be awake at any given point in time. To address this problem, this paper proposes a centralized and distributed asynchronous broadcast algorithm that achieves minimal broadcast latency and redundancy. In addition, it uses a novel asynchronous MAC protocol that ensures all neighbors of a broadcasting node are awake to receive a broadcast. The performance of our algorithms is evaluated under different network configurations. We show via extensive simulation studies that our algorithms have near optimal network performance in terms of broadcast latency. In particular, compared to OTAB, the best broadcast scheduling algorithm to date, the broadcast latency and transmission times achieved by our designs are 1/5 and 1/2 that of OTAB, respectively.