14 research outputs found
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
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
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
Internet Traffic based Channel Selection in Multi-Radio Multi-Channel Wireless Mesh Networks
Wireless Mesh Networks(WMNs) are the outstanding technology to facilitate wireless broadband Internet access to users. Routers in WMN have multiple radio interfaces to which multiple orthogonal/partially overlapping channels are assigned to improve the capacity of WMN. This paper is focused on channel selection problem in WMN since proper channel selection to radio interfaces of mesh router increases the performance of WMN. To access the Internet through WMN, the users have to associate with one of the mesh routers. Since most of the Internet Servers are still in wired networks, the major dominant traffic of Internet users is in downlink direction i.e. from the gateway of WMN to user. This paper proposes a new method of channel selection to improve the user performance in downlink direction of Internet traffic. The method is scalable and completely distributed solution to the problem of channel selection in WMN. The simulation results indicate the significant improvement in user performance
On the number of channels required for interference-free wireless mesh networks
We study the problem of achieving maximum network throughput with fairness among the flows at the nodes in a wireless mesh network, given their location and the number of their half-duplex radio interfaces. Our goal is to find the minimum number of non-overlapping frequency channels required to achieve interference-free communication. We use our existing Select x for less than x topology control algorithm (TCA) to build the connectivity graph (CG), which enhances spatial channel reuse to help minimize the number of channels required. We show that the TCA-based CG approach requires fewer channels than the classical approach of building the CG based on the maximum power. We use multi-path routing to achieve the maximum network throughput and show that it provides better network throughput than the classical minimum power-based shortest path routing. We also develop an effective heuristic method to determine the minimum number of channels required for interference-free channel assignment
Interference mitigation in wireless mesh networks through radio co-location aware conflict graphs
Wireless Mesh Networks (WMNs) have evolved into a wireless communication technology of immense interest. But technological advancements in WMNs have inadvertently spawned a plethora of network performance bottlenecks, caused primarily by the rise in prevalent interference. Conflict Graphs are indispensable tools used to theoretically represent and estimate the interference in wireless networks. We propose a generic algorithm to generate conflict graphs which is independent of the underlying interference model. Further, we propose the notion of radio co-location interference, which is caused and experienced by spatially co-located radios in multi-radio multi-channel WMNs. We experimentally validate the concept, and propose a new all-encompassing algorithm to create a radio co-location aware conflict graph. Our novel conflict graph generation algorithm is demonstrated to be significantly superior and more efficient than the conventional approach, through theoretical interference estimates and comprehensive experiments. The results of an extensive set of ns-3 simulations run on the IEEE 802.11g platform strongly indicate that the radio co-location aware conflict graphs are a marked improvement over their conventional counterparts. We also question the use of total interference degree as a reliable metric to predict the performance of a Channel Assignment scheme in a given WMN deployment
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