Enhanced Dynamic Bandwidth Allocation Algorithm for Intelligent Home Networks

Internet of Things (IoT) has been seen playing a tremendous change in the Information Technology (IT) environments, and thus its importance has also been realized and played a vital role within Intelligent Home Networks (IHNs). This is because IoT establishes a connection between things and the Internet by utilizing different sensing devices to implement the intelligence to deal with the identification and management of the connected things. IHNs use intelligent systems to perform their daily operations. Meanwhile, these networks ensure comfort, safety, healthcare, automation, energy conservation, and remote management to devices and users. Apart from that, these networks provide assistance in self-healing for faults, power outages, reconfigurations, and more. However, we have realized that more and advanced devices and services continue to be introduced and used in these networks. This has led to competitions of the limited available network resources, services, and bandwidth. In this paper, therefore, we present the design and implementation of a Novel Dynamic Bandwidth Allocation (NoDBA) algorithm to solve the performance bottleneck incurred with IHNs. The proposed algorithm deals with the management of bandwidth and its allocation. In the proposed algorithm, this study integrates two algorithms, namely; Offline Cooperative Algorithm (OCA) and Particle Swarm Optimization (PSO) to improve Quality of Service (QoS). PSO defines the priority limits for subnets and nodes in the network. Meanwhile, OCA facilitates dynamic bandwidth allocation in the network. The Network Simulator-2 (NS-2) was used to simulate and evaluate the NoDBA and it showed improved results compared to the traditional bandwidth allocation algorithms. The obtained results show an average throughput of 92%, average delay of 0.8 seconds, and saves energy consumption of 95% compared to Dynamic QoS-aware Bandwidth Allocation (DQBA) and Data-Driven Allocation (DDA).   Keywords: IHNs, Dynamic Bandwidth Allocation, PSO, OCA, Qo

ZigBee Healthcare Monitoring System for Ambient Assisted Living Environments

Healthcare Monitoring Systems (HMSs) are promising to monitor patients in hospitals and elderly people living in Ambient Assisted Living environments using Wireless Sensor Networks. HMSs assist in monitoring chronic diseases such as Heart Attacks, High Blood Pressure and other cardiovascular diseases. Wearable and implanted devices are types of Body sensors that collect human health related data. Collected data is sent over Personal Area Networks (PANs). However, PANs are facing the challenge of increasing network traffic due to the increased number of IP-enabled devices connected in Healthcare Monitoring Systems to assist patients. ZigBee technology is an IEEE 802.15.4 standard designed to address network traffic issues in PANs. To route traffic, ZigBee network use ZigBee Tree Routing (ZTR) protocol. ZTR however suffers a challenge of network latency caused by end to end delay during packet forwarding. This paper is proposing a New Tree Routing Protocol (NTRP) for Healthcare Monitoring Systems to collect Heart Rate signals. NTRP uses Kruskal’s minimum spanning tree to find shortest routes on a ZigBee network which improves ZTR. Neighbor tables are implemented in NTRP instead of parent–child mechanism implemented in ZTR. To reduce end to end delay, NTRP groups’ nodes into clusters and the cluster heads use neighbor tables to forward heart rate data to the destination node. NS-2 simulation tool is used to evaluate NTRP performance