Radio Co-location Aware Channel Assignments for Interference Mitigation in Wireless Mesh Networks

Designing high performance channel assignment schemes to harness the potential of multi-radio multi-channel deployments in wireless mesh networks (WMNs) is an active research domain. A pragmatic channel assignment approach strives to maximize network capacity by restraining the endemic interference and mitigating its adverse impact on network performance. Interference prevalent in WMNs is multi-faceted, radio co-location interference (RCI) being a crucial aspect that is seldom addressed in research endeavors. In this effort, we propose a set of intelligent channel assignment algorithms, which focus primarily on alleviating the RCI. These graph theoretic schemes are structurally inspired by the spatio-statistical characteristics of interference. We present the theoretical design foundations for each of the proposed algorithms, and demonstrate their potential to significantly enhance network capacity in comparison to some well-known existing schemes. We also demonstrate the adverse impact of radio co- location interference on the network, and the efficacy of the proposed schemes in successfully mitigating it. The experimental results to validate the proposed theoretical notions were obtained by running an exhaustive set of ns-3 simulations in IEEE 802.11g/n environments.Comment: Accepted @ ICACCI-201

Reliable Prediction of Channel Assignment Performance in Wireless Mesh Networks

The advancements in wireless mesh networks (WMN), and the surge in multi-radio multi-channel (MRMC) WMN deployments have spawned a multitude of network performance issues. These issues are intricately linked to the adverse impact of endemic interference. Thus, interference mitigation is a primary design objective in WMNs. Interference alleviation is often effected through efficient channel allocation (CA) schemes which fully utilize the potential of MRMC environment and also restrain the detrimental impact of interference. However, numerous CA schemes have been proposed in research literature and there is a lack of CA performance prediction techniques which could assist in choosing a suitable CA for a given WMN. In this work, we propose a reliable interference estimation and CA performance prediction approach. We demonstrate its efficacy by substantiating the CA performance predictions for a given WMN with experimental data obtained through rigorous simulations on an ns-3 802.11g environment.Comment: Accepted in ICACCI-201

Near Optimal Channel Assignment for Interference Mitigation in Wireless Mesh Networks

In multi-radio multi-channel (MRMC) WMNs, interference alleviation is affected through several network design techniques e.g., channel assignment (CA), link scheduling, routing etc., intelligent CA schemes being the most effective tool for interference mitigation. CA in WMNs is an NP-Hard problem, and makes optimality a desired yet elusive goal in real-time deployments which are characterized by fast transmission and switching times and minimal end-to-end latency. The trade-off between optimal performance and minimal response times is often achieved through CA schemes that employ heuristics to propose efficient solutions. WMN configuration and physical layout are also crucial factors which decide network performance, and it has been demonstrated in numerous research works that rectangular/square grid WMNs outperform random or unplanned WMN deployments in terms of network capacity, latency, and network resilience. In this work, we propose a smart heuristic approach to devise a near-optimal CA algorithm for grid WMNs (NOCAG). We demonstrate the efficacy of NOCAG by evaluating its performance against the minimal-interference CA generated through a rudimentary brute-force technique (BFCA), for the same WMN configuration. We assess its ability to mitigate interference both, theoretically (through interference estimation metrics) and experimentally (by running rigorous simulations in NS-3). We demonstrate that the performance of NOCAG is almost as good as the BFCA, at a minimal computational overhead of O(n) compared to the exponential of BFCA

Predicting Performance of Channel Assignments in Wireless Mesh Networks through Statistical Interference Estimation

Wireless Mesh Network (WMN) deployments are poised to reduce the reliance on wired infrastructure especially with the advent of the multi-radio multi-channel (MRMC) WMN architecture. But the benefits that MRMC WMNs offer viz., augmented network capacity, uninterrupted connectivity and reduced latency, are depreciated by the detrimental effect of prevalent interference. Interference mitigation is thus a prime objective in WMN deployments. It is often accomplished through prudent channel allocation (CA) schemes which minimize the adverse impact of interference and enhance the network performance. However, a multitude of CA schemes have been proposed in research literature and absence of a CA performance prediction metric, which could aid in the selection of an efficient CA scheme for a given WMN, is often felt. In this work, we offer a fresh characterization of the interference endemic in wireless networks. We then propose a reliable CA performance prediction metric, which employs a statistical interference estimation approach. We carry out a rigorous quantitative assessment of the proposed metric by validating its CA performance predictions with experimental results, recorded from extensive simulations run on an ns-3 802.11g environment

Enhancing Channel Assignment Performance in Wireless Mesh Networks Through Interference Mitigation Functions

The notion of Total Interference Degree (TID) is traditionally used to estimate the intensity of prevalent interference in a Multi-RadioMulti-ChannelWirelessMesh Network (MRMC WMN). Numerous Channel Assignment (CA) approaches, linkscheduling algorithms and routing schemes have been proposed for WMNs which rely entirely on the concept of TID estimates. They focus on minimizing TID to create a minimal interference scenario for the network. In our prior works [1] and [2], we have questioned the efficacy of TID estimate and then proposed two reliable interference estimation metrics viz., Channel Distribution Across Links Cost (CDALcost) and Cumulative X-Link-Set Weight (CXLSwt). In this work, we assess the ability of these interference estimation metrics to replace TID as the interferenceminimizing factor in a CA scheme implemented on a grid MRMC WMN. We carry out a comprehensive evaluation on ns-3 and then conclude from the results that the performance of the network increases by 10-15% when the CA scheme uses CXLSwt as the underlying Interference Mitigation Function (IMF) when compared with CA using TID as IMF. We also confirm that CDALcost is not a better IMF than TID and CXLSwt.Comment: 6 Page

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

Characterization,Estimation, and Mitigation of Interference in Multi- Radio Multi- Channel Wireless Mesh Networks

Wireless Mesh Networks (WMNs) have evolved into a wireless communication technology of im-mense interest. But technological advancements in WMNs have inadvertently spawned a plethora of network performance bottlenecks, caused primarily by the rise in prevalent interference. The benefits that multi-radio multichannel(MRMC) WMNs offer viz., augmented network capacity, uninterrupted connectivity and reduced latency, are depreciated by the detrimental effect of prevalent interference. Interference mitigation is thus a prime objective in WMN deployments. Conflict Graphs are indispensable tools used to theoretically represent and estimate the interference in wire- less networks. This interference is multidimensional, radio co-location interference (RCI) being a crucial aspect that is seldom addressed in conflict graph generation approaches suggested in re- search studies. Further, designing high performance channel assignment (CA) schemes to harness the potential of MRMC deployments in WMNs is an active research domain. A pragmatic channel assignment approach strives to maximize network capacity by restraining the endemic interference and mitigating its adverse impact on network performance metrics. However, numerous CA schemes have been proposed in research literature and there is a lack of CA performance prediction techniques which could assist in choosing a suitable CA for a given WMN

Interference Mitigation Based on Radio Aware Channel Assignment for Wireless Mesh Networks

© 2018, Springer Science+Business Media, LLC, part of Springer Nature. An intricate network deployment for high demand users leads to simultaneous transmission in wireless mesh networks. Multiple radios are adapted to individual nodes for improving network performance and Quality of Service (QoS). However, whenever multiple radios are assigned to the same channel, co-located radio interference occurs, which poses a major drawback. This paper proposes a Radio aware Channel Assignment (Ra-CA) mechanism based on a direct graphical model for mitigation of interference in multi-radio multi-channel networks. Initially, the co-located radio interference is identified by classifying non-interfering links for simultaneous transmission in the network. Proposed channel assignment mechanism helps in allocating the minimal number of channels to the network that mitigate co-located radio interference. Performance analysis of the proposed Ra-CA strategy is carried out compared with other existing techniques, like Breadth First Search-Channel Assignment (BFS-CA) and Maximal Independent Set Channel Assignment (MaIS-CA), in multi-radio networks. Simulation results demonstrate that the proposed channel assignment scheme is more efficient compared to the existing ones, in terms of QoS parameters like, packet drop rate, packet delivery ratio, transmission delay and throughput