Energy and channel transmission management algorithm for resource harvesting body area networks

Abstract

In body area networks, sustainable energy supply and reliable data transmission are important to prolong the service cycle and guarantee the quality of service. In this article, we build a system model to capture the stochastic processes in body area networks, including energy harvesting process, spectrum pricing process, and data sampling process. In the system model, energy harvesting technology and cognitive radio technology are adopted to provide green energy and improve transmission environment for body area networks. Based on the proposed model, we formulate an optimization problem of system utility maximization. Since this problem is a multi-objective mixed-integer problem under multiple restrictions, we decompose the problem into several subproblems by Lyapunov optimization theory. Based on this, we design an efficient online energy and channel transmission management algorithm to solve these subproblems and achieve a close-to-optimal system utility without any priori knowledge. We analyze the optimality of proposed algorithm and derive the required battery capacity and the size of data buffer. Simulation results demonstrate the effectiveness of the proposed algorithm.

FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks

“…Moreover, in order to improve the transmission environment, the context-aware algorithm needs to process heavy computing tasks and manage large amounts of information. On the contrary, context-ignorant routing algorithms [2,4,6,11,13,14] that don't utilize the contextual information of nodes are more likely to execute the flooding transmission in opportunistic social networks. Because of the existence of superfluous message group copies in the network, the context-ignorant routing algorithm commonly has very high end-to-end delay and network overhead.…”

“…In opportunistic networks, nodes in unpredictable locations attempt to communicate with each other at unpredictable intervals. Nowadays, the application areas of opportunistic networks mainly include wildlife monitoring networks [5], interplanetary networks [6,7], vehicular networks [8], networks in underdeveloped areas [9,10], and social opportunistic networks [11][12][13][14]. At the dawn of 5G networks and big data, technological development is leading to the wide distribution of mobile devices, such as smartphones, Bluetooth, Wi-Fi technologies, or notebooks.…”

An Efficient Task Scheduling Strategy Utilizing Mobile Edge Computing in Autonomous Driving Environment

“…But the arrival of the 5G network further improves the practicality of MEC. Due to the high speed (transmission rate up to 10G/s), low latency (transmission delay is less than 1ms) of this 5G network, the data can be exchanged between the vehicle and the ECS within a few milliseconds [13][14][15]. Therefore, the combination of 5G and MEC can satisfy autonomous driving tasks owing to high-performance computing and low network latency.…”

Predict and Forward: An Efficient Routing-Delivery Scheme Based on Node Profile in Opportunistic Networks

“…In recent years, the research on opportunity networks mainly focuses on the routing algorithm [5,6,10,12,13], and several innovative routing algorithms are proposed for different application scenarios in opportunistic networks. Consequently, in this section, we will give a brief introduction to the state-of-the-art of both two-phase and profile-based routing algorithms in opportunistic networks.…”

“…In recent years, with the rapid development of novel wireless devices, such as mobile phones, smart watches, Bluetooth earphones or other wearable sensor devices, the message applications in opportunistic social networks [3,4] may obtain more opportunities to communicate with each other. Moreover, the hot issues of opportunistic networks include routing algorithms [5][6][7], mobile models [8,9], security and cooperation [1,10], and applications [11,12].…”