a distributed load balancing approach for industrial ieee 802.11 wireless networks

A Distributed Load Balancing Approachfor Industrial IEEE 802.11 Wireless

Networks

A Distributed Load Balancing Approachfor Industrial IEEE 802.11 Wireless

Networks

2014 YU-ANTL Seminal

Hyun dong HwangAdvanced Networking Technology Lab. (YU-ANTL)

Dept. of Information & Comm. Eng, Graduate School, Yeungnam University, KOREA

(Tel : +82-53-810-3940; Fax : +82-53-810-4742http://antl.yu.ac.kr/; E-mail : [email protected])

http://antl.yu.ac.kr/

Advanced Networking Tech. Lab.Yeungnam University (YU-ANTL)

YU-ANTL Lab SeminalHyun dong Hwang2

Outline

Introduction System Model Dynamic Load Balancing Algorithm

Performance Evaluation First scenario Second scenario

Conclusions and Future Works



Introduction

Introduction Load balancing is a technique used to balance traffic flows in IEEE

wireless networks in order to increase throughput. When network load exceeds, or is close to its maximum capacity,

congestion occurs and throughput decreases. load balancing technique comes into play when different APs

cover the same area or there is an overlapping area where hosts can choose to connect to, at least, two APs.

Load balancing approaches classification Centralized approach

Pros : Ensures devices interoperability. Cons : Entire system failure, while network size increases, even central

node load processing increases at the expense of its efficiency. Distributed approach

Pros : Fault-tolerant, not require the use of additional network entities for APs management

Cons : coordination need among APs in order to ensure information in-tegrity, accuracy and consistency about network status.



Introduction

Selection and transfer techniques : About the selection of the new station, two approaches can be used Random selection : AP is randomly chosen as candidate for

transfer Pros : Technique is simple to implement and does not require high

computational time Cons : It may not be the best for load balance achieving in the short-

est possible time. Best candidate : the most appropriate station is selected taking

into account load metrics like traffic information generated by the station itself, packet loss and the average network traffic. Threshold-based : AP can accept a station association request if an

established load metric does not exceed a threshold value decided a priori

Relative threshold : load metric is evaluated considering other APs load and then the best one is chosen



Introduction

Load displacement mechanisms There are three basic approaches for load control

Association management– Overloaded AP can send a dissociation frame to an already associated sta-

tion, hoping for a re-association to another AP more appropriate Admission control– AP can simply refuse new association requests if there is overload risk. The

request can be accepted only if predicted load is less than a threshold value Coverage adjustment– Overloaded APs can reduce transmission power of their beacon frame in or-

der to be hardly detected by new stations



System Model

Current shortcoming In industrial networks, packets transmission is strictly related to

real-time constraints. Existing load balancing approaches, de-scribed in the previous section, are based on load metrics like throughput, packets loss or number of connected stations.

However, in industrial wireless networks (soft real-time), system efficiency can’t be measured only by throughput or packets loss percentage.

It’s necessary to evaluate QoS performances in terms of num-ber of deadline miss for each station in a given moment.



System Model

Reference paper “Dynamic load balancing techniques for flexible wireless indus-

trial networks” Dynamic load balancing approach used in industrial real-time con-

texts. Each AP, connected to the backbone, communicates with a network

controller having a global network view and realizes corrective ac-tions in case of performances degradation.

This approach presents the same problems of centralized load balanc-ing algorithm described previously.(hardware architecture must be complex in terms of computational costs.)



System Model

Propose system model Load balancing decisions are performed by each AP, in a dis-

tributed way, and not by a network controller only. Main approach is to provide a mechanism for load distribution

in order to obtain less deadline miss possible, lower than a tol-erable threshold.



System Model

Propose dynamic Load balancing (Dynamic Load Bal-ancing Algorithm : DLBA) Load metric takes into account the number of Deadline Miss

(DM) measured by each station.



Dynamic Load Balancing Algorithm

DLBA runs inside each AP in a distributed manner, chose a station from connected stations list.

Station handle condition Signal quality is lower than a

given threshold value. This occurs when a station is moving from an AP towards another one and have to perform handover to not lose connectivity.

DM exceeds a threshold value. In this case, the wireless channel is too busy, collisions cause delivery delays of soft real-time traffic flows and number of deadline miss increases.




Select Access Point Algorithm APs exchange each other network

information through the wired backbone, the DLBA evaluates network information of APs de-tected by managed station and signal quality that it detects.

The algorithm verifies if detected signal level is enough for connec-tion, performing a control with a threshold value.

Measures best performances, in terms of deadline miss of con-nected stations, is chosen.




Handover Algorithm



Performance Evaluation

Test System Routers/APs Cisco Linksys WRT54GL(Linux system, openWRT)

First scenario 2 Linksys router in AP mode and connected through a wired

backbone Packet size is 5152 byte and transmission period was set to 10

ms, equal to relative deadline. 600 packets for second are transmitted




Throughput/Workload versus Packet Error Rate per-centage




DeadLine Miss measured(1)




Second scenario




Scenario 2: Throughput/Workload vs. Packet Error rate percentage




HOSTS MEAN DEADLINE MISS RATIO USING DLBA



Conclusions and Future Works

The use of load metrics like workload are acceptable only when communications among nodes are not characterized by real-time constraints typical of industrial process control.

APs must always ensure best performances and react to system degradations. To this end, we have chosen Deadline Miss (DM) as load metric in a distributed approach.

Network load is equally distributed based on number of deadline miss detected by each host and on signal power of each AP. Results, obtained through measures in some real scenarios, are very promising and show significant im-provements compared to not real-time approaches and real-time centralized approaches.



Reference

[1] IEEE Standard for Local and metropolitan area networks – part 16: Air interface for Broadband Wireless Access System, 2009.[2] A. Balachandran, P. Bahl, G. M. Voelker, “Hot-Spot Congestion Relief in Public-area Wireless Networks,” Proc. of 4th IEEE Workshop on Mobile Computing Systems and Applications, June 2002.[3] H. Velayos, V. Aleo, and G. Karlsson, “Load Balancing in Overlapping Wireless LAN Cells,” in proc. of IEEE ICC’04, pp. 3833–3836, 2004.[4] H.M. ElBadawy, “Ptimal RAT selection algorithm trhough Common radio resource management in heterogeneous wireless networks”, 28th National Radio Science Conference (NRSC), pp. 1-9, 2011[5] Xu Fengyuan, C.C. Tan, Li Qun, Yan Guanhua, Wu Jie, “Designing a Practical Access Point Association Protocol”, Proc of IEEE INFOCOM 2010, pp 1-9, 2010[6] Kuo-Shu Huang, I-Ping Hsieh, Shang-Juh Kao, “Incorporating AP selection and call admission control for seamless handoff procedure”, International Conference on Computer and Communication Engineering, pp. 823-826, 2008

a distributed load balancing approach for industrial ieee 802.11 wireless networks

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