A Review of Multi-Channel Medium Access Control Protocols for Wireless Sensor Networks

Mobile devices may use mobile edge computing to improve energy efficiency and responsiveness by offloading computation tasks to edge servers. However, the transmissions of mobile devices may result in interference that decreases the upload rate and prolongs transmission delay. Clustering has been shown as an effective approach to improve the transmission efficiency for dense devices, but there is no distributed algorithm for the optimization of clustering and computation offloading. In this work, we study the optimization problem of computation offloading to minimize the energy consumption of mobile devices in mobile edge computing by adaptively clustering devices to improve the transmission efficiency. To address the optimization problem in a distributed manner, the decision problem of clustering and computation offloading for mobile devices is formulated as a potential game. We introduce the construction of the potential game and show the existence of Nash equilibrium in the game with a finite enhancement ability. Then, we propose a distributed algorithm of clustering and computation offloading based on game theory. We conducted a simulation to evaluate the proposed algorithm. The numerical results from our simulation show that our algorithm can improve offloading efficiency for mobile devices in mobile edge computing by improving transmission efficiency. By offloading more tasks to edge servers, both the energy efficiency of mobile devices and the responsiveness of computation-intensive applications can be improved simultaneously.

Section: Introductionmentioning

confidence: 99%

Computation Offloading and User-Clustering Game in Multi-Channel Cellular Networks for Mobile Edge Computing

Huang

Wang

2023

“…Wireless sensor devices (WSDs) have emerged in various applications of smart cities, remote healthcare, unmanned aerial vehicle (UAV) and smart homes [1][2][3][4][5], where WSDs generate and transmit remote sensing data to sink nodes. Various types of modern sensor devices may generate a great volume of data [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Although edge computing could increase the efficiency of processing computation tasks for WSDs, the rapidly increasing WSDs may cause radio communication interference to result in longer communication delays when these WSDs offload their tasks to the edge server simultaneously. Currently, multi-channel communication has been applied to several applications of WSDs to enhance the performance of both transmission throughput and energy efficiency [2]. The communication interference can thus be avoided by allocating one channel to each WSD.…”

Section: Introductionmentioning

confidence: 99%

Computation Offloading Game for Multi-Channel Wireless Sensor Networks

Wang

2022

Computation offloading for wireless sensor devices is critical to improve energy efficiency and maintain service delay requirements. However, simultaneous offloadings may cause high interferences to decrease the upload rate and cause additional transmission delay. It is thus intuitive to distribute wireless sensor devices in different channels, but the problem of multi-channel computation offloading is NP-hard. In order to solve this problem efficiently, we formulate the computation offloading decision problem as a decision-making game. Then, we apply the game theory to address the problem of allowing wireless sensor devices to make offloading decisions based on their own interests. In the game theory, not only are the data size of wireless sensor devices and their computation capability considered but the channel gain of each wireless sensor device is also included to improve the transmission rate. The consideration could evenly distribute wireless sensor devices to different channels. We prove that the proposed offloading game is a potential game, where the Nash equilibrium exists in each game after all device states converge. Finally, we extensively evaluate the performance of the proposed algorithm based on simulations. The simulation results demonstrate that our algorithm can reduce the number of iterations to achieve Nash equilibrium by 16%. Moreover, it improves the utilization of each channel to effectively increase the number of successful offloadings and lower the energy consumption of wireless sensor devices.

“…The focus of this study is on ad hoc network characteristic-decentralized topologies with nodes communicating as peers between themselves. In an ad hoc network, a single channel needs to be shared by several nodes, and the medium access control (MAC) protocol [8][9][10] is responsible for the coordination between nodes. With advances in technological development, the physical (PHY) layer is vastly improved with higher data rates and a better quality of service (QoS) [11][12][13][14].…”

mentioning

confidence: 99%

An Adaptive and Spectrally Efficient Multi-Channel Medium Access Control Protocol for Dynamic Ad Hoc Networks

Beg

Mostafa

AbdulGhaffar

et al. 2022

Medium access control (MAC) protocols in ad hoc networks have evolved from single-channel independent transmission mechanisms to multi-channel concurrent mechanisms to efficiently manage the demands placed on modern networks. The primary aim of this study is to compare the performance of popular multi-channel MAC (MMAC) protocols under saturated network traffic conditions and propose improvements to the protocols under these conditions. A novel, dynamically adaptive MMAC protocol was devised to take advantage of the performance capabilities of the evaluated protocols in changing wireless ad hoc network conditions. A simulation of the familiar MAC protocols was developed based on a validated simulation of the IEEE 802.11 standard. Further, the behaviors and performances of these protocols are compared against the proposed MMAC protocols with a varying number of ad hoc stations and concurrent wireless channels in terms of throughput, Jain’s fairness index, and channel access delay. The results show that the proposed MMAC protocol, labeled E-SA-MMAC, outperforms the existing protocols in throughput by up to 11.9% under a constrained number of channels and in channel access delays by up to 18.3%. It can be asserted from these observations that the proposed approach provides performance benefits against its peers under saturated traffic conditions and other factors, such as the number of available wireless channels, and is suitable for dynamic ad hoc network deployments.