A demand-based slot assignment algorithm for energy-aware reliable data transmission in wireless sensor networks

This paper proposes a new demand-based slot assignment (DSA) algorithm that allocates time slots based on the bandwidth demand of each node in a tree topology. DSA is basically different from SDA, DAS, or WIRES that assigns one large slot for each sensor node, but is similar to the frame-slot pair assignment (FSA) algorithm used in TreeMAC in that it assigns multiple small size slots for sensor nodes per each data collection round. DSA tackles the shortcomings of FSA in terms of the capability of packet aggregation and filtering, the balance of energy consumption, and bandwidth utilization. In general, nodes at lower tree depths process more packets and consume more energy than ones at higher tree depths, and thus the imbalanced energy consumption shortens network lifetime. The proposed algorithm allocates a sequence of receiving slots and then a sequence of sending slots to each node. This approach not only reduces the power consumption of nodes at lower depths significantly by allowing efficient data aggregation and filtering, but also it improves bandwidth utilization by removing wasted slots. In addition, the RTS and CTS messages are used within a slot for ensuring the reliability of data transmission and updating sync time between a child and its parent. Simulation results show that DSA far outperforms FSA in energy consumption and bandwidth utilization.     

Achieving energy‐neutral data transmission by adjusting transmission power for energy‐harvesting wireless sensor networks

Recently, benefiting from rapid development of energy harvesting technologies, the research trend of wireless sensor networks has shifted from the battery‐powered network to the one that can harvest energy from ambient environments. In such networks, a proper use of harvested energy poses plenty of challenges caused by numerous influence factors and complex application environments. Although numerous works have been based on the energy status of sensor nodes, no work refers to the issue of minimizing the overall data transmission cost by adjusting transmission power of nodes in energy‐harvesting wireless sensor networks. In this paper, we consider the optimization problem of deriving the energy‐neutral minimum cost paths between the source nodes and the sink node. By introducing the concept of energy‐neutral operation, we first propose a polynomial‐time optimal algorithm for finding the optimal path from a single source to the sink by adjusting the transmission powers. Based on the work earlier, another polynomial‐time algorithm is further proposed for finding the approximated optimal paths from multiple sources to the sink node. Also, we analyze the network capacity and present a near‐optimal algorithm based on the Ford–Fulkerson algorithm for approaching the maximum flow in the given network. We have validated our algorithms by various numerical results in terms of path capacity, least energy of nodes, energy ratio, and path cost. Simulation results show that the proposed algorithms achieve significant performance enhancements over existing schemes. Copyright © 2016 John Wiley & Sons, Ltd.     

移动无线传感网的生存时间优化算法研究

当sink节点位置固定不变时,分布在sink 节点周围的传感节点很容易成为枢纽节点,因转发较多的数据而过早失效。为解决上述问题,提出移动无线传感网的生存时间优化算法（LOAMWSN）。LOAMWSN算法考虑sink节点的移动,采用减聚类算法确定sink节点移动的锚点,采用最近邻插值法寻找能遍历所有锚点的最短路径近似解,采用分布式非同步Bellman-Ford算法构建sink节点k跳通信范围内的最短路径树。最终,传感节点沿着最短路径树将数据发送给sink节点。仿真结果表明：在节点均匀分布和非均匀分布的无线传感网中,LOAMWSN算法都可以延长网络生存时间、平衡节点能耗,将平均节点能耗保持在较低水平。在一定的条件下,比Ratio_w、TPGF算法更优。     

Routing protocol over lossy links for ISA100.11a industrial wireless networks

This paper proposes novel routing and topology control algorithms for industrial wireless sensor networks (IWSNs) based on the ISA100.11a standard. The proposed algorithms not only reduces energy consumption at the node level but also reduces packet latency at the network level. Using the residual energy and packet reception rate of neighbor nodes, the source node can estimate the highest election weight. Hence, packets are conveyed by a multi-hop forwarding scheme from source nodes to the sink by the optimal path. Furthermore, energy consumption and network latency are minimized using integer linear programming. Simulation results show that the proposed algorithms are fully effective in terms of energy conservation and network latency for IWSNs.     

无线传感器网络的一种低功耗拓扑控制算法DSPT

针对无线传感器网络环境下拓扑控制问题,提出一种基于最小成本路径的分布式拓扑控制算法,其基本思想是:针对无线传感器网络many-to-one的通讯模型,建立以Sink节点为根节点的拓扑控制树,使得整个网络的通讯成本最低,从而延长网络的生命周期,与传统Ad Hoc网络采用的最小生成树拓扑控制算法相比较,具有低功耗,算法时间复杂低,易于实现等特点。仿真结果表明,在节点稠密部署情况下,无线传感器网络的整体功耗比MST生成树降低25%,关键节点的功耗比MST生成树降低13%。     

A myopic mobile sink migration strategy for maximizing lifetime of wireless sensor networks

Network lifetime maximization is challenging particularly for large-scale wireless sensor networks. The sensor nodes near the sink node tend to suffer high energy consumption due to heavy traffic relay operations, becoming vulnerable to energy depletion. The rationale of the sink mobility approach is that as the sink node moves around, such risk of energy depletion at some nodes can be alleviated. In this paper, we first obtain the optimal mobile sink sojourning pattern by solving a linear programming model and then we mathematically analyze why the optimal solution exhibits such sojourning pattern. We use the insights from this analysis to design a simple practical heuristic algorithm for sink mobility, which utilizes only local information. Our heuristic is very different from the existing algorithms which often use the traffic volume as the main decision factor, in that we consider the variance of residual energy of neighboring sensor nodes. The simulation results show that our scheme achieves near-optimal network lifetime even with the relatively low moving speed of the mobile sink.     

A mobile sink path planning for wireless sensor networks based on priority‐ordered dependent nonparametric trees

The professional design of the routing protocols with mobile sink(s) in wireless sensor networks (WSNs) is important for many purposes such as maximizing energy efficiency, increasing network life, and evenly distributing load balance across the network. Moreover, mobile sinks ought to first collect data from nodes which have very important and dense data so that packet collision and loss can be prevented at an advanced level. For these purposes, the present paper proposes a new mobile path planning protocol by introducing priority‐ordered dependent nonparametric trees (PoDNTs) for WSNs. Unlike traditional clustered or swarm intelligence topology‐based routing methods, a topology which has hierarchical and dependent infinite tree structure provides a robust link connection between nodes, making it easier to reselect ancestor nodes (ANs). The proposed priority‐ordered infinite trees are sampled in the specific time frames by introducing new equations and hierarchically associated with their child nodes starting from the root node. Hence, the nodes with the highest priority and energy that belong to the constructed tree family are selected as ANs with an opportunistic approach. A mobile sink simply visits these ANs to acquire data from all nodes in the network and return to where it started. As a result, the route traveled is assigned as the mobile path for the current round. We have performed comprehensive performance analysis to illustrate the effectiveness of the present study using NS‐2 simulation environment. The present routing protocol has achieved better results than the other algorithms over various performance metrics.     

Utilizing Neighbours-Table to Improve Tree Routing Protocol in ZigBee Network

ZigBee is an industrial standard for wireless ad hoc networks based on IEEE 802.15.4. It has been developed for low cost, low data rate and low power consumption. ZigBee??s network layer defines two routing protocols namely Ad Hoc On-demand Distance Vector and Tree Routing (TR). TR protocol follows the tree topology (parent?Cchild) in forwarding the data packets from source nodes to the sink node. However, the source does not find rather nor the location of the sink is close to the source node or if it is not in the sub-tree. In this case it will follow the tree topology which will use a lot of hops to deliver data packets to the sink node. This paper present an improvement of TR protocol for ZigBee network and is called Improved Tree Routing (ImpTR) protocol which is computationally simple in discovering the better path to transmit data packets to the sink node, and does not need any addition in hardware. ImpTR determines the better path to the sink node depending on the tables of the neighbouring nodes, which is part of the existing ZigBee network specification. Results show that the proposed algorithm provides shorter average end-to-end delay, increase throughput, decrease the average number of hops and decrease the energy consumption from the network when compared to the original TR routing protocol.     

Traffic-based topology control algorithm for energy savings in multi-hop wireless networks

This paper presents a traffic-based topology control algorithm for multi-hop wireless networks, in order to optimize the global energy consumption while maximizing the aggregate throughput. Contrary to major related works, we do not consider that reducing transmission powers implies reducing interferences and that the traffic is uniformly distributed among the links. Thus, we propose to dynamically calculate the transmission power of nodes depending on the traffic. First, we redefine the N-hop interference model for varying transmission powers. Then, we define a function giving the minimum interference according to the transmission powers. We propose several algorithms minimizing this function: global optimization, local optimization, and distributed optimization for a limited computation cost. Our first algorithm is used as a reference for limited cases. We show by simulation that our heuristics are relevant compared to existing works.     

Minimum-energy all-to-all multicasting in wireless ad hoc networks

A wireless ad hoc network consists of mobile nodes that are powered by batteries. The limited battery lifetime imposes a severe constraint on the network performance, energy conservation in such a network thus is of paramount importance, and energy efficient operations are critical to prolong the lifetime of the network. All-to-all multicasting is one fundamental operation in wireless ad hoc networks, in this paper we focus on the design of energy efficient routing algorithms for this operation. Specifically, we consider the following minimum-energy all-to-all multicasting problem. Given an all-to-all multicast session consisting of a set of terminal nodes in a wireless ad hoc network, where the transmission power of each node is either fixed or adjustable, assume that each terminal node has a message to share with each other, the problem is to build a shared multicast tree spanning all terminal nodes such that the total energy consumption of realizing the all-to-all multicast session by the tree is minimized. We first show that this problem is NP-Complete. We then devise approximation algorithms with guaranteed approximation ratios. We also provide a distributed implementation of the proposed algorithm. We finally conduct experiments by simulations to evaluate the performance of the proposed algorithm. The experimental results demonstrate that the proposed algorithm significantly outperforms all the other known algorithms.     

Random Mobility and Heterogeneity-Aware Hybrid Synchronization for Wireless Sensor Network

Random mobility of a node in wireless sensor networks (WSNs) causes the frequent changes in the network dynamics with increased cost in terms of energy and bandwidth. During data collections and transmission, they need the additional efforts to synchronize and schedule the activities of nodes. A key challenge is to maintain the global clock scale for synchronization of nodes at different levels to minimize the energy consumption and clock skew. It is also difficult to schedule the activities for effective utilization of slots allocated for aggregated data transmission. The paper proposes the Random Mobility and Heterogeneity-aware Hybrid Synchronization Algorithm (MHS) for WSN. The proposed algorithm uses the cluster-tree for efficient synchronization of CH and nodes in the cluster and network, level-by-level. The network consists of three nodes with random mobility and are heterogeneous regarding energy with static sink. All the nodes and CH are synchronized with the notion of the global timescale provided by the sink as a root node. With the random mobility of the node, the network structure frequently changes causing an increase in energy consumption. To mitigate this problem, MHS aggregate data with the notion of a global timescale throughout the network. Also, the hierarchical structure along with pair-wise synchronization reduces the clock skews hence energy consumption. In the second phase of MHS, the aggregated data packets are passed through the scheduled and synchronized slots using TDMA as basic MAC layer protocol to reduce the collision of packets. The results are extended by using the hybrid approach of scheduling and synchronization algorithm on the base protocol. The comparative results show that MHS is energy and bandwidth efficient, with increased throughput and reduced delay as compared with state-of-the-art solutions.     

Dual head static clustering algorithm for wireless sensor networks

Clustering of nodes is often used in wireless sensor networks to achieve data aggregation and reduce the number of nodes transmitting the data to the sink. This paper proposes a novel dual head static clustering algorithm (DHSCA) to equalise energy consumption by the sensor nodes and increase the wireless sensor network lifetime. Nodes are divided into static clusters based on their location to avoid the overhead of cluster re-formation in dynamic clustering. Two nodes in each cluster, selected on the basis of the their residual energy and their distance from the sink and other nodes in the cluster, are designated as cluster heads, one for data aggregation and the other for data transmission. This reduces energy consumption during intra-cluster and inter-cluster communication. A multi-hop technique avoiding the hot-spot problem is used to transmit the data to the sink. Experiments to observe the energy consumption patterns of the nodes and the fraction of packets successfully delivered using the DHSCA suggest improvements in energy consumption equalisation, which, in turn, enhances the lifetime of the network. The algorithm is shown to outperform all the other static clustering algorithms, while being comparable with the performance of the best dynamic algorithm.     

Power-efficient and interference-free link scheduling algorithms for connected wireless sensor networks

A fundamental aspect in performance engineering of wireless sensor networks (WSN) is optimizing the set of links that can be concurrently activated to meet a given signal-to-interference-plus-noise ratio (SINR) threshold. The solution of this combinatorial problem is a key element in wireless link scheduling. Another key architectural goal in WSN is connectivity. The connectivity of sensor nodes is critical for WSN, as connected graphs can be used for both data collection and data dissemination. In this paper, we investigate the joint scheduling and connectivity problem in WSN assuming the SINR model. We propose algorithms to build connected communication graphs with power-efficient links to be scheduled simultaneously in one time slot. The algorithms aiming at minimizing the number of time slots needed to successfully schedule all the given links such that the nodes can communicate without interference in the SINR model. While power-efficient and interference-free schedules reduce energy consumption, minimization of the schedule length (shortest link scheduling) has the effect of maximizing network throughput. We propose one greedy randomized constructive heuristic, two local search procedures, and three greedy randomized adaptive search procedures metaheuristics. We report computational experiments comparing the effectiveness of the proposed algorithms. Our simulation also shows the trade-off between power consumption and schedule length and the results indicate that not only the overall performance of our algorithms, but also show that the total power and schedule length value of its solutions are better than the existing work.

     

Energy efficient clustering algorithms for wireless sensor networks: novel chemical reaction optimization approach

Clustering has been accepted as one of the most efficient techniques for conserving energy of wireless sensor networks (WSNs). However, in a two-tiered cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving data from their member sensor nodes, aggregating them and transmitting that data to the base station (BS). Therefore, proper selection of CHs and optimal formation of clusters play a crucial role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient CH selection and energy balanced cluster formation algorithms, which are based on novel chemical reaction optimization technique (nCRO), we jointly called these algorithms as novel CRO based energy efficient clustering algorithms (nCRO-ECA). These algorithms are developed with efficient schemes of molecular structure encoding and potential energy functions. For the energy efficiency, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes in the CH selection phase. In the cluster formation phase, we consider various distance and energy parameters. The algorithm is tested extensively on various scenarios of WSNs by varying number of sensor nodes and CHs. The results are compared with original CRO based algorithm, namely CRO-ECA and some existing algorithms to demonstrate the superiority of the proposed algorithm in terms of energy consumption, network lifetime, packets received by the BS and convergence rate.     

基于最优刚性图的能量有效分布式拓扑控制算法

针对现有无线传感器网络拓扑控制算法无法平衡各节点能量消耗的问题,基于最优刚性图提出了一种具有平衡负载特性的能量有效分布式拓扑控制算法。算法引入综合反映能量消耗及剩余能量两方面因素的链路权值函数,能够根据当前节点剩余能量实时地动态优化拓扑结构,从而有效地平衡网络节点的能量消耗。从理论上证明了优化后的拓扑是2?连通的而且具有稀疏性;同时优化后拓扑中各节点的平均度趋于4。仿真结果表明,与其他算法相比,该算法能够有效地平衡各节点的能量消耗,进而延长网络生命期。     

Flow-balanced routing for multi-hop clustered wireless sensor networks

Power efficiency and coverage preservation are two important performance metrics for a wireless sensor network. However, there is scarcely any protocol to consider them at the same time. In this paper, we propose a flow-balanced routing (FBR) protocol for multi-hop clustered wireless sensor networks that attempts to achieve both power efficiency and coverage preservation. The proposed protocol consists of four algorithms, one each for network clustering, multi-hop backbone construction, flow-balanced transmission, and rerouting. The proposed clustering algorithm groups several sensors into one cluster on the basis of overlapping degrees of sensors. The backbone construction algorithm constructs a novel multi-level backbone, which is not necessarily a tree, using the cluster heads and the sink. Furthermore, the flow-balanced routing algorithm assigns the transferred data over multiple paths from the sensors to the sink in order to equalize the power consumption of sensors. Lastly, the rerouting algorithm reconstructs the network topology only in a place where a head drops out from the backbone due to the head running out of its energy. Two metrics called the network lifetime and the coverage lifetime are used to evaluate the performance of FBR protocol in comparison with previous ones. The simulation results show that FBR yields both much longer lifetime and better coverage preservation than previous protocols. For example, FBR yields more than twice network lifetime and better coverage preservation than a previous efficient protocol, called the coverage-preserving clustering protocol (CPCP) [18], when the first sensor dies and the network coverage is kept at 100%, respectively.     

A Comparative Analysis of Flat,Hierarchical and Location-Based Routing in Wireless Sensor Networks

In this article, we are going to discuss the comparison of three different categories of routing principles, namely, flat routing, hierarchical routing and location-based routing in Wireless Sensor Networks. Under the flat routing strategies, we are going to discuss 1-D flooding and 2-D flooding. Under the hierarchical category, we will explore spanning tree and under the location-based routing category, we will use angle-based dynamic path construction. For all these four algorithms, on the basis of a precise energy modelling and MAC layer modelling, comparison is made out on the basis of energy consumption and delay incurred for the transmission of data from the sensing nodes via the forwarding nodes and ultimately converging at the sink node. Also, retransmission probability, an important criterion, is taken into consideration and its effect on energy consumption and end-to-end delay is observed.     

A Game Theoretical Approach for Topology Control in Wireless Ad Hoc Networks with Selfish Nodes

In ad hoc networks, a significant amount of energy available to devices is utilized in network management operations. Since devices have limited energy resources, therefore, they drop data packets of other nodes to reduce their energy consumption. This selfish behaviour increases number of retransmissions over the link which increases energy consumption of the source node, introduces time delays, and degrades throughput of the network. Although conventional distributed topology control solutions minimize energy utilization of the nodes by adjustment of transmission power, however, selfish behaviour by devices introduce additional complexity in design which make topology control a challenging task. In this paper, we proposed Energy Efficient Topology Control Algorithm (EETCA) using game theoretical approach, in which, utility of the node depends on selfishness of the neighbors, link traffic rate, and link length. In decision-making step, nodes remove the links with other nodes that have high drop rate under the condition that network remains connected. We show that Nash Equilibrium point of the proposed game results in Pareto optimal network topology. We compare results of EETCA with Optimum (OPT) and Minimum Least Power Path Tree (MLPT) algorithms presented in literature. We carried our simulations under multiple sources scenario which show that EETCA outperforms previous approaches when number of nodes in the network increases. Furthermore, we simulate the performance of Ad-hoc On-demand Distance Vector (AODV) routing protocol under EETCA topology and compare it with MLPT and OPT topologies. The results show that the ad hoc network constructed using proposed solution substantially improves throughput of AODV routing protocol as compared to MLPT and OPT topology control algorithms.     

Localized Interference-aware and Energy-conserving Topology Control Algorithms

Energy conservation and interference reduction are the two ultimate goals of topology control in wireless multihop networks. However, the existing energy-conserving algorithms rarely consider interference reduction or at most consider it implicitly. It has been proved that the power-efficient topology does not guarantee low interference. Considering that in any topology, the nodes affected by the communications between any other nodes should be as few as possible, we propose in this article two algorithms, the interference-aware local minimum spanning tree (MST) based algorithm (IALMST) and the interference-bounded energy-conserving algorithm (IBEC). In IALMST, each node builds its local MST independently according to the costs of interference and energy consumption, while in IBEC, each node commonly selects the edge with the least energy consumption, and only when the interference exceeds a predefined bound, it is allowed to select a more expensive edge to reduce interference. Theoretical analysis and simulations illustrate that both algorithms can effectively conserve energy and reduce interference.

An Automatic Presence Service for Low Duty-Cycled Mobile Sensor Networks

We consider providing presence service for duty-cycled wireless sensor networks through a multihop approach. The presence service is to ensure automatic network monitoring by which each node would know whether the sink node is reachable or not. Towards providing such presence service, we tackle three problems: 1) efficient neighbor discovery due to not-always-awake nature of duty-cycling and the mobile environment, 2) light presence message passing from the sink node to all reachable nodes given broadcasting is expensive and difficult in an embedded duty-cycling network, and 3) automatic network monitoring if there is node failure and network partition. In our protocol, in order to save power consumption, an online node which is reachable from the sink node only book-keeps the broadcast schedule of its parent in a breadth-first-search spanning tree in order to trace the online status all along. The offline node which is not reachable from the sink node stays awake periodically based on quorum-based wakeup scheduling, and probes the beacons which may come from online nodes. The presence protocol can automatically detect link failure or network partition, and it can also automatically recover online status for each sensor node if there is a path to the sink node, which is significant for applications that are sensitive to end-to-end latency constraints. The presence protocol proposed is implemented through a layered approach so that it is independent from any specific MAC and routing protocols. We make extensive simulations in order to validate the energy efficiency and reliability of our design.