Performance evaluation of interference aware topology power and flow control channel assignment algorithm

Multi-Radio Multi-Channel Wireless Mesh Network (MRMC-WMN) has been considered as one of the key technology for the enhancement of network performance. It is used in a number of real-time applications such as disaster management system, transportation system and health care system. MRMC-WMN is a multi-hop network and allows simultaneous data transfer by using multiple radio interfaces. All the radio interfaces are typically assigned with different channels to reduce the effect of co-channel interference. In MRMC-WMN, when two nodes transmit at the same channel in the range of each other, generates co-channel interference and degrades the network throughput. Co-channel interference badly affects the capacity of each link that reduces the overall network performance. Thus, the important task of channel assignment algorithm is to reduce the co-channel interference and enhance the network performance. In this paper, the problem of channel assignment has been addressed for MRMC-WMN. We have proposed an Interference Aware, Topology, Power and Flow Control (ITPFC) Channel Assignment algorithm for MRMC-WMN. This algorithm assignes the suitable channels to nodes, which provides better link capacity and reduces the co-channel interference. In the previous work performance of the proposed algorithm has been evaluated for a network of 30 nodes. The aim of this paper is to further evaluate the performance of proposed channel assignment algorithm for 40 and 50 nodes network. The results obtained from these networks show the consistent performance in terms of throughput, delay, packet loss and number of channels used per node as compared to LACA, FCPRA and IATC Channel Assignment algorithms

A Socio-inspired CALM Approach to Channel Assignment Performance Prediction and WMN Capacity Estimation

A significant amount of research literature is dedicated to interference mitigation in Wireless Mesh Networks (WMNs), with a special emphasis on designing channel allocation (CA) schemes which alleviate the impact of interference on WMN performance. But having countless CA schemes at one's disposal makes the task of choosing a suitable CA for a given WMN extremely tedious and time consuming. In this work, we propose a new interference estimation and CA performance prediction algorithm called CALM, which is inspired by social theory. We borrow the sociological idea of a "sui generis" social reality, and apply it to WMNs with significant success. To achieve this, we devise a novel Sociological Idea Borrowing Mechanism that facilitates easy operationalization of sociological concepts in other domains. Further, we formulate a heuristic Mixed Integer Programming (MIP) model called NETCAP which makes use of link quality estimates generated by CALM to offer a reliable framework for network capacity prediction. We demonstrate the efficacy of CALM by evaluating its theoretical estimates against experimental data obtained through exhaustive simulations on ns-3 802.11g environment, for a comprehensive CA test-set of forty CA schemes. We compare CALM with three existing interference estimation metrics, and demonstrate that it is consistently more reliable. CALM boasts of accuracy of over 90% in performance testing, and in stress testing too it achieves an accuracy of 88%, while the accuracy of other metrics drops to under 75%. It reduces errors in CA performance prediction by as much as 75% when compared to other metrics. Finally, we validate the expected network capacity estimates generated by NETCAP, and show that they are quite accurate, deviating by as low as 6.4% on an average when compared to experimentally recorded results in performance testing

Joint Traffic-Aware UAV Placement and Predictive Routing for Aerial Networks

Aerial networks, composed of Unmanned Aerial Vehicles (UAVs) acting as Wi-Fi access points or cellular base stations, are emerging as an interesting solution to provide on-demand wireless connectivity to users, when there is no network infrastructure available, or to enhance the network capacity. This article proposes a traffic-aware topology control solution for aerial networks that holistically combines the placement of UAVs with a predictive and centralized routing protocol. The synergy created by the combination of the UAV placement and routing solutions allows the aerial network to seamlessly update its topology according to the users' traffic demand, whilst minimizing the disruption caused by the movement of the UAVs. As a result, the Quality of Service (QoS) provided to the users is improved. The components of the proposed solution are described and evaluated individually in this article by means of simulation and an experimental testbed. The results show that all the components improve the QoS provided to the users when compared to the corresponding baseline solutions

Inter-flow and intra-flow interference mitigation routing in wireless mesh networks

International audienceIn this paper, we address the problem of QoS support in an heterogeneous multi-rate wireless mesh network. We propose a new routing metric that provides information about link quality, based on PHY and MAC characteristics, including the link availability, the loss rate and the available bandwidth. This metric allows to apprehend inter-flow interferences and avoid bottleneck formation by balancing traffic load on the links. Based on the conflict graph model and calculation of maximal cliques, we define a method to estimate the available bandwidth of a path which considers, in addition, intra-flow interferences. Finally, we propose a routing protocol that supports this metric and we study by simulation its performances compared to different existing routing metrics and protocols. The results revealed the ability of our protocol (LARM) to support the network scalability as well as its ability to choose routes with high throughput and limited delay, thus, better delivery of data traffic