A Distributed Load Balancing Approach for Industrial IEEE 802.11 Wireless Networks

1. 2014 YU-ANTL Seminal A Distributed Load Balancing Approachfor Industrial IEEE 802.11 Wireless Networks Hyun dong Hwang Advanced Networking Technology Lab. (YU-ANTL) Dept. of Information & Comm. Eng, Graduate School, Yeungnam University, KOREA (Tel : +82-53-810-3940; Fax : +82-53-810-4742 http://antl.yu.ac.kr/; E-mail : mch2d@hotmail.com)

2. Outline • Introduction • System Model • Dynamic Load Balancing Algorithm • Performance Evaluation • First scenario • Second scenario • Conclusions and Future Works

3. 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 integrity, accuracy and consistency about network status.

4. 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 shortest 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

5. 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 station, 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 order to be hardly detected by new stations

6. System Model • Current shortcoming • In industrial networks, packets transmission is strictly related to real-time constraints. Existing load balancing approaches, described 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 number of deadline miss for each station in a given moment.

7. System Model • Reference paper • “Dynamic load balancing techniques for flexible wireless industrial networks” • Dynamic load balancing approach used in industrial real-time contexts. • Each AP, connected to the backbone, communicates with a network controller having a global network view and realizes corrective actions in case of performances degradation. • This approach presents the same problems of centralized load balancing algorithm described previously.(hardware architecture must be complex in terms of computational costs.)

8. System Model • Propose system model • Load balancing decisions are performed by each AP, in a distributed 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 tolerable threshold.

9. System Model • Propose dynamic Load balancing (Dynamic Load Balancing Algorithm : DLBA) • Load metric takes into account the number of Deadline Miss (DM) measured by each station.

10. 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.

11. Dynamic Load Balancing Algorithm • Select Access Point Algorithm • APs exchange each other network information through the wired backbone, the DLBA evaluates network information of APs detected by managed station and signal quality that it detects. • The algorithm verifies if detected signal level is enough for connection, performing a control with a threshold value. • Measures best performances, in terms of deadline miss of connected stations, is chosen.

12. Dynamic Load Balancing Algorithm • Handover Algorithm

13. 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

14. Performance Evaluation

15. Performance Evaluation • Throughput/Workload versus Packet Error Rate percentage

16. Performance Evaluation • DeadLine Miss measured(1)

17. Performance Evaluation • DeadLine Miss measured(2)

18. Performance Evaluation • Second scenario

19. Performance Evaluation • Scenario 2: Throughput/Workload vs. Packet Error rate percentage

20. Performance Evaluation • HOSTS MEAN DEADLINE MISS RATIO USING DLBA

21. 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 improvements compared to not real-time approaches and real-time centralized approaches.

22. Performance Evaluation • DeadLine Miss measured(1)

23. 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”, Procof 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