Efficient information gathering from large wireless sensor networks

大型无线传感器网络有效信息收集

Computer Communications, Volume 132, November 2018, Pages 84-95

Mohammed Amine Merzoug, Azzedine Boukerche, Ahmed Mostefaoui

摘要：Considering large WSNs and comparing data aggregation approaches in terms of scalability, robustness, completeness, and time/energy effectiveness, recent research has asserted the superiority of serial structure-free approaches over serial structure-based ones, and over both parallel structure-free and parallel structure-based techniques. But, in spite of the fact that serial structure-free approaches excel in large and medium-scale networks, their underlying path-construction algorithms are not optimal and can be improved by reducing the involved communications and further shortening the visiting path. To respond to this need, this paper presents Geometric Serial Search (GSS); a new serial structure-free algorithm specifically designed to efficiently gather information from large wireless resource-constrained networks. In addition to its completeness (i.e., visiting all nodes), collision-free nature, high scalability, energy/time efficiency, and robustness against topology changes (failures in links/nodes, …), the main advantage distinguishing GSS is that it considerably reduces communications and always approaches the optimal number of hops. More precisely, in GSS, no control packets or complex data structures are required, instead, one packet hops from node to node and explores the entire network. While gradually finding its way through the network, this packet interrogates nodes and collects their responses at the same time. The followed path is not established in advance, can stem from any node in the network, and requires only the one-hop neighborhood information of each traversed node to be gradually drawn. The obtained OMNeT++ simulation results presented in this paper demonstrate the efficiency of GSS and confirm all the previously cited claims.

Distributed trajectory design for data gathering using mobile sink in wireless sensor networks  

基于移动sink的无线传感器网络数据收集分布式轨迹设计

AEU - International Journal of Electronics and Communications, Volume 96, November 2018, Pages 1-12

Areej Alsaafin, Ahmed M. Khedr, Zaher Al Aghbari

摘要：Several studies have demonstrated the benefits of using a mobile sink (MS) to reduce energy consumption resulting from multi-hop data collection using a static sink in wireless sensor networks (WSNs). However, using MS may increase data delivery latency as it needs to visit each sensor node in the network to collect data. This is a critical issue in delay-sensitive applications where all sensed data must be gathered within a given time constraint. In this paper, we propose a distributed data gathering protocol utilizing MS for WSNs. The proposed protocol designs a trajectory for the MS, which minimizes energy consumption and delay. Our protocol operates in four main phases: data sensing, rendezvous point (RP) selection, trajectory design, and data gathering. In data sensing, a number of deployed sensor nodes keep sensing the target field for a specific period of time to capture events. Then, using a cluster-based RP selection algorithm, some sensor nodes are selected to become RPs based on local information. The selected RPs are then used to determine a trajectory for the MS. To do so, we propose three trajectory design algorithms that support different types of applications, namely reduced energy path (REP), reduced delay path (RDP), and delay bound path (DBP). The MS moves through the constructed path to accomplish its data gathering according to an effective scheduling technique that is introduced in this work. We validate the proposed protocol via extensive simulations over several metrics such as energy, delay, and time complexity.

Connectivity and coverage based protocols for wireless sensor networks  

基于连通性与覆盖的无线传感器网络协议

Ad H oc Networks, Volume 80, November 2018, Pages 54-69

Azzedine Boukerche, Peng Sun

摘要：A wireless sensor network (WSN) consists of a group of energy-constrained sensor nodes with the ability of both sensing and communication, which can be deployed in a field of interest (FoI) for detecting or monitoring some special events, and then forwarding the aggregated data to the designated data center through sink nodes or gateways. In this case, whether the WSN can keep the FoI under strict surveillance and whether the WSN can gather and forward the desired information are two of the most fundamental problems in wireless sensor networks that need to be solved. Therefore, preserving network connectivity while maximizing coverage by using the limited number of energy constrained nodes is the most critical problem for the deployment of WSNs. In this survey article, we classify and summarize the state-of-the-art algorithms and techniques that address the connectivity-coverage issues in the wireless sensor networks.

Efficient sensor network management for asset localization  

“资产”本地化的有效传感器网络管理

Computers & Operations Research, Volume 99, November 2018, Pages 148-165

Andrei Soeanu, Sujoy Ray, Jean Berger, Mourad Debbabi

摘要：Asset localization represents an important application over wireless sensor networks (WSN) with a wide area of applicability ranging from network surveillance to search and rescue operations. In this paper, we address a research problem of network management where resource constrained sensors, in terms of capacity, sensing range and energy, are assigned to multiple targets in order to optimally localize assets with minimized error. We consider a heterogeneous network of omnidirectional sensors, each of which has an individual capacity to focus on a number of targets and a specific range to accurately estimate its distances to the targets that it is focusing on. A proper localization of each target requires a minimum of K (typically three) sensors where the target location is estimated using the intersection of the K range circles. We further analyze the problem under the constraint of a globally specified overall WSN energy budget which limits the possible assignments for the capacitated sensors. Restricting the energy budget leads to a trade-off between energy conservation and localization performance. In this context, we propose a heuristic solution approach leveraging evolutionary learning followed by meta-heuristic improvements based on target swapping among sensors. This approach actually minimizes a quantifier that is composed of the total localization area for all targets in addition to a penalty for each target if it is assigned less than minimum sensors. We provide an illustrative case study for the proposed approach and assess its effectiveness experimentally via benchmark results obtained on a data-set derived from known vehicle routing problem instances.

Software-defined wireless sensor networks: A survey  

软件定义无线传感器网络综述

Journal of Network and Computer Applications, Volume 119, 1 October 2018, Pages 42-56

Habib Mostafaei, Michael Menth

摘要：Software-defined networking (SDN) decouples data and control plane, i.e., forwarding elements are remotely configured by centralized controllers instead through distributed control protocols. Wireless sensor networks (WSNs) have mostly been controlled in a distributed way, but its configuration challenges are complex and can be theoretically better solved with network-wide knowledge – the solution just needs to be configured on the distributed sensor nodes. This calls for SDN in WSNs and so that software-defined WSNs (SD-WSNs) have been proposed. In this survey, we explain basics of WSN and SDN, describe fundamentals of SD-WSNs and how SDN can improve the operation of WSN. Furthermore, we outline the open challenges that need to be investigated in more detail and discuss lessons learned during the preparation this survey.