BorderSense: Border patrol through advanced wireless sensor networks

Sun, Zhi; Wang, Pu; Vuran, Mehmet C.; Al-Rodhaan, Mznah; Akyildiz, Ian F.

doi:10.1016/j.adhoc.2010.09.008

Cited by 277 publications

(119 citation statements)

References 38 publications

Supporting

Mentioning

118

Contrasting

Unclassified

Order By: Relevance

“…Barrier coverage with wireless sensors concentrates on detecting intruders that attempt to penetrate a specific area [18], [19], where a chain of sensor nodes are deployed on or along the virtual border to form a network [20]. With the requirement of protecting sensitive facilities and national borders increasing, barrier coverage has a growing number of applications.…”

Section: Related Workmentioning

confidence: 99%

Problem Specific MOEA/D for Barrier Coverage with Wireless Sensors

Zhang

Lee

et al. 2016

IEEE Trans. Cybern.

View full text Add to dashboard Cite

Abstract-Barrier coverage with wireless sensors aims at detecting intruders who attempt to cross a specific area, where wireless sensors are distributed remotely at random. This paper considers limited-power sensors with adjustable ranges deployed along a linear domain to form a barrier to detect intruding incidents. We introduce three objectives to minimize: 1) total power consumption while satisfying full coverage; 2) the number of active sensors to improve the reliability; and 3) the active sensor nodes' maximum sensing range to maintain fairness. We refer to the problem as the tradeoff barrier coverage (TBC) problem. With the aim of obtaining a better tradeoff among the three objectives, we present a multiobjective optimization framework based on multiobjective evolutionary algorithm (MOEA)/D, which is called problem specific MOEA/D (PS-MOEA/D). Specifically, we define a 2-tuple encoding scheme and introduce a cover-shrink algorithm to produce feasible and relatively optimal solutions. Subsequently, we incorporate problem-specific knowledge into local search, which allows search procedures for neighboring subproblems collaborate each other. By considering the problem characteristics, we analyze the complexity and incorporate a strategy of computational resource allocation into our algorithm. We validate our approach by comparing with four competitors through several most-used metrics. The experimental results demonstrate that PS-MOEA/D is effective and outperforms the four competitors in all the cases, which indicates that our approach is promising in dealing with TBC.Index Terms-Barrier coverage, evolutionary algorithms, multiobjective optimization, wireless sensor networks (WSNs).

show abstract

Section: Related Workmentioning

confidence: 99%

Problem Specific MOEA/D for Barrier Coverage with Wireless Sensors

Zhang

Lee

et al. 2016

IEEE Trans. Cybern.

View full text Add to dashboard Cite

show abstract

“…Underground sensor networks consist of sensors that are buried in and communicate through dense materials like soil or concrete. Such networks can be used for soil moisture reporting in agriculture [43], infrastructure supervision, intrusion detection [44] and transport systems [45]. Underwater sensor networks rely on immersed sensors and are used in a variety of applications such as ocean supervision [46], water quality monitoring [47], disaster prevention, surveillance [48] and pipeline monitoring.…”

Section: Underground and Underwater Sensor Networkmentioning

confidence: 99%

Energy efficiency in wireless sensor networks: A top-down survey

Rault¹,

Bouabdallah²,

Challal³

2014

Computer Networks

804

452

View full text Add to dashboard Cite

The design of sustainable wireless sensor networks (WSNs) is a very challenging issue. On the one hand, energyconstrained sensors are expected to run autonomously for long periods. However, it may be cost-prohibitive to replace exhausted batteries or even impossible in hostile environments. On the other hand, unlike other networks, WSNs are designed for specific applications which range from small-size healthcare surveillance systems to large-scale environmental monitoring. Thus, any WSN deployment has to satisfy a set of requirements that differs from one application to another. In this context, a host of research work has been conducted in order to propose a wide range of solutions to the energysaving problem. This research covers several areas going from physical layer optimization to network layer solutions. Therefore, it is not easy for the WSN designer to select the efficient solutions that should be considered in the design of application-specific WSN architecture.We present a top-down survey of the trade-offs between application requirements and lifetime extension that arise when designing wireless sensor networks. We first identify the main categories of applications and their specific requirements. Then we present a new classification of energy-conservation schemes found in the recent literature, followed by a systematic discussion as to how these schemes conflict with the specific requirements. Finally, we survey the techniques applied in WSNs to achieve trade-off between multiple requirements, such as multi-objective optimisation.

show abstract

“…Networks of small unmanned aerial vehicles 1 (UAVs) can also be employed for wildfire monitoring [1], border surveillance [2], and for extending ad hoc networks on the ground [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Routing For Flying Ad Hoc Networks

Aarthi¹,

Santhi²

2017

International Journal of Advanced Research in Computer and Comm

View full text Add to dashboard Cite

Abstract-This paper reports experimental results on self-organizing wireless networks carried by small flying robots. Flying ad hoc networks (FANETs) composed of small unmanned aerial vehicles (UAVs) are flexible, inexpensive and fast to deploy. This makes them a very attractive technology for many civilian and military applications. Due to the high mobility of the nodes, maintaining a communication link between the UAVs is a challenging task. The topology of these networks is more dynamic than that of typical mobile ad hoc networks (MANETs) and of typical vehicle ad hoc networks (VANETs). As a consequence, the existing routing protocols designed for MANETs partly fail in tracking network topology changes.In this work, we compare two different routing algorithms for ad hoc networks: optimized link-state routing (OLSR), and predictive-OLSR (P-OLSR). The latter is an OLSR extension that we designed for FANETs; it takes advantage of the GPS information available on board. To the best of our knowledge, P-OLSR is currently the only FANET-specific routing technique that has an available Linux implementation. We present results obtained by both Media Access Control (MAC) layer emulations and real-world experiments. In the experiments, we used a testbed composed of two autonomous fixed-wing UAVs and a node on the ground. Our experiments evaluate the link performance and the communication range, as well as the routing performance.Our emulation and experimental results show that P-OLSR significantly outperforms OLSR in routing in the presence of frequent network topology changes.

show abstract

BorderSense: Border patrol through advanced wireless sensor networks

Cited by 277 publications

References 38 publications

Problem Specific MOEA/D for Barrier Coverage with Wireless Sensors

Problem Specific MOEA/D for Barrier Coverage with Wireless Sensors

Energy efficiency in wireless sensor networks: A top-down survey

Dynamic Routing For Flying Ad Hoc Networks

Contact Info

Product

Resources

About