MAEB: Routing Protocol for IoT Healthcare

Abstract

<p class="MsoNormal"> <span lang="EN-US">Healthcare is one of the most promising applications of Internet of Things. This paper describes a prototype for the IoT healthcare systems. We propose the Movement-Aided Energy-Balance (MAEB) routing protocol. The movement and energy information of the neighbor Coordinators </span><span lang="EN-US">are</span><span lang="EN-US"> collected and stored in the neighbor discovery procedure. The MAEB forwarding is used to select the most suitable neighbor to forward the data. The simulation results show that the proposed protocol has better performance than the other three routing protocols.</span><span lang="EN-US"><o:p></o:p></span> </p

Sensors for Context-Aware Smart Healthcare: A Security Perspective

“…Routing protocols must also be resilient to attackers who can inject malicious routing information into the network (e.g., when a node is captured) to cause routing inconsistencies and disrupt communications. Numerous studies have been defined to secure routing protocols within sensor networks, based on the trustworthiness of neighbour nodes, clustering or hierarchical methods and genetic evolutionary techniques [ 399 , 400 , 401 , 402 ].…”

Highly Reliable Routing In Healthcare Systems Based on Internet of Things

“…In the maximum allowable number of error burst (MAEB) algorithm, the source node rst calculates an equation for every neighbour and then selects a node with a smaller value of the equation as the next hop for information transmission [14]. The process of calculating k nodes in the MAEB algorithm is as follows:…”

Energy-Aware Mobile Edge Computing for Low-Latency Visual Data Processing

“…To further improve energy-efficiency more recent works on clustering routing such as in [29] utilize users' mobility for selecting cluster heads which are then used to route packtes toward the Gateway. However, such cluster heads take some time to scan neighboring nodes' signals and store their information to form clusters.…”

“…δ is the attenuation order of obstacles' potential fields that has been shown empirically to give best performance when δ ∈ [1, 2] [34]; and o j corresponds to the obstacle j potential intensity induced by the destination node d as following: [23][24][25][26][27][28][29]. This mode is initially proposed by [35] and has been shown to guarantee (both practically and theoretically) packets delivery when the minimization function f CHAPTER 4.…”