An Enhanced Scheme in Controlling Both Coverage and Quality of Service in Wireless Sensor Networks

Abstract

With the increasing number of applications for Wireless Sensor Networks (WSNs), different Quality of Services (QoS) levels based on the type of applications are required. An increasing research interest has been noted in the provision of QoS support in WSNs. QoS support in WSNs is challenging because of very limited resources, such as battery power, processing power, memory, and bandwidth. An earlier study introduced a QoS control approach based on the Gur Game. The Gur Game-based scheme can maintain QoS without knowing the total number of sensors. However, the Gur Game-based scheme does not consider the active sensor coverage. The problems of collecting redundant data and wasting bandwidth and battery energy arise if active sensors are distributed too densely or too sparsely. Therefore, this study proposes a Coverage-Aware QoS Control (CAQC) to achieve both QoS and coverage control using an enhanced reward function. Simulations that compared our scheme with previous studies in various environments indicated that CAQC creates a robust sensor network capable of achieving both QoS and coverage targets.

A High-Robust Sensor Activity Control Algorithm for Wireless Sensor Networks

“…Many studies have been conducted on the different aspects of QoS of sensor networks, such as power-saving [11][12][13][14][15][16][17][18][19], routing [20][21][22][23][24][25][26], throughput of networks [27], enhancement performance [28,29] and coverage [30][31][32], and. The main goal of this study was to autonomously control the number of active sensors.…”

“…In the multi-objective QoS control algorithm, the authors combined the two control objectives of QoS and coverage and proposed a compound control method that can control the coverage ratio in addition to QoS [30]. In [19,31,32], combining the two control objectives of QoS and node density, the control strategies for rectangular, circular, and various elliptical regions are given, and a dynamic adjustment mechanism based on the Gur Game algorithm is designed.…”

A High-robust Sensor Activity Control Algorithm for Wireless Sensor Networks

“…Many studies have been conducted on the different aspects of QoS of sensor networks, such as power-saving [10][11][12][13][14][15], routing [16][17][18][19], coverage [22][23][24][25], and throughput of networks [26]. The main goal of this study was to autonomously control the number of active sensors.…”

“…In the multi-objective QoS control algorithm, the authors combined the two control objectives of QoS and coverage and proposed a compound control method that can control the coverage rate in addition to QoS [22]. In [23][24][25],…”

Intelligent Transduction for Response Synthesis in Telemanipulation

“…This gives a strong sense of relative object approach which is more effective than vision based approaches as a view by itself needs to be augmented with contextual interpretation aid [30] [31]. Verification of the method is possible by using a laboratory version slave robot instrumented without interconnect encumbrance similar to that devised for wireless monitoring of utilities [32] as the wireless sensor networks are evolving with better functionality [33]. The transduction method developed here can also work with interfaces such as the electro-hydraulic type actuators [34] for heavy duty applications.…”