Multi-hop wireless networks and Routing management, it has is a vital and challenging resource allocation technique in Scheduling process. A distributed low-complexity scheduling algorithm develops into more challenging tasks, even if taking into account a physical interference model. At previous years a number of scheduling algorithms were presented, but pre-existing scheduling algorithm does not solve the drawbacks to implement in multi hop networks to overcome these issues, proposed a new scheduling approach Ant Colony Optimization Max-Weight Scheduling (ACO-MWS) for scheduling and routing in multi-hop wireless networks. The combination of proposed approaches such as ACO Algorithm and Max-Weight Scheduling that overcome the pre-existing scheduling problems and it accomplish maximum throughput at the distributed low complexity. The performance evolution of ACO, Max-Weight, and ACOMWS are presented in this paper.

Wireless Ad Hoc Network, Heavy Tail, Ant Colony Optimization, Max-Weight Scheduling, Throughput, Routing

[1]. G. Gupta and N. B. Shroff, “Delay analysis of scheduling policies in wireless networks,” Asilomar Conference on Signals, Systems, and Computers, Oct. 2008.
[2]. A. Stolyar, “Large deviations of queues under QoS scheduling algorithms,” Allerton 2006, Sept. 2006.
[3]. M. Neely, “Delay analysis for maximal scheduling in wireless networks with bursty traffic,” IEEE INFOCOM 2008.
[4]. M. Neely, “Order optimal delay for opportunistic scheduling in multiuser wireless uplinks and downlinks,” Allerton 2006, Sept. 2006.
[5]. M. Neely, “Delay analysis for max weight opportunistic scheduling in wireless systems,” Allerton 2008, Sept. 2008.
[6]. L. Bui, R. Srikant, and A. Stolyar, “Novel architecture and algorithms for delay reduction in back-pressure scheduling and routing,” IEEE INFOCOM 2009.
[7]. L. Tassiulas and A. Ephremides, “Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks,” IEEE Transactions on Automatic Control, vol. 37, no. 12, pp. 1936–1948, Dec 1992.
[8]. A. Ganti, E. Modiano, J.N. Tsitsiklis (2007). Optimal transmission scheduling in symmetric communication models with intermittent connectivity. IEEE Transactions on Information Theory, 53(3), pp. 998-1008.
[9]. L. Georgiadis, M. Neely, L. Tassiulas (2006). Resource allocation and cross-layer control in wireless networks. Foundations and Trends in Networking, 1(1), pp. 1-144.
[10]. A. Gut (2005). Probability: a Graduate Course. Springer Texts in Statistics, Springer- erlag.
[11]. B. Ji, C. Joo, N.B. Shro_ (2013). Throughput-optimal scheduling in multihop wireless networks without per-ow information. IEEE/ACM Transactions on Networking, 21(2), pp. 634-647.
[12]. B. Ji, C. Joo, N.B. Shro_ (2013). Delay-based Back-Pressure scheduling in multihop wireless networks. IEEE/ACM Transactions on Networking, 21(5), pp. 1539-1552.
[13]. D. Bertsimas, D. Gamarnik, J.N. Tsitsiklis (2001). Performance of multiclass Markovian queueing networks via piecewise linear Lyapunov functions. The Annals of Applied Probability, 11(4), pp. 1384-1428.
[14]. X. Lin and N. B. Shroff, “The Impact of Imperfect Scheduling on Cross-Layer Congestion Control in Wireless Networks,” IEEE/ACM Transactions on Networking, vol. 14, no. 2, pp. 302–315, April 2006.
[15]. L. Tassiulas and A. Ephremides, “Stability Properties of Constrained Queueing Systems and Scheduling Policies for Maximal Throughput in Multihop Radio Networks,” IEEE Transactions on Automatic Control, vol. 37, no. 12, pp. 1936–1948, December 1992.
[16]. B. Hajek and G. Sasaki, “Link Scheduling in Polynominal Time,” IEEE Transactions on Information Theory, vol. 34, no. 5, September 1988.
[17]. S. Sarkar and L. Tassiulas, “End-to-end Bandwidth Guarantees Through Fair Local Spectrum Share in Wireless Ad-hoc Networks,” in IEEE CDC, December 2003.
[18]. P. Chaporkar, K. Kar, and S. Sarkar, “Throughput Guarantees in Maximal Scheduling in Wireless Networks,” in the 43rd Annual Allerton Conference on Communication, Control and Computing, September 2005.
[19]. X. Wu and R. Srikant, “Bounds on the Capacity Region of Multihop Wireless Networks Under Distributed Greedy Scheduling,” in IEEE INFOCOM, April 2006.
[20]. G. Sharma, N. B. Shroff, and R. R. Mazumdar, “On the Complexity of Scheduling in Wireless Networks,” in ACM Mobicom, September 2006.
[21]. L. Tassiulas and A. Ephremides, “Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks,” IEEE Trans. Automatic Control, vol. 37, no. 12, pp. 1936-1948, Dec. 1992.
[22]. Dorigo M, Birattari M, Stutzle T, Bruxelles D, Roosevelt AF. Ant colony optimization artificial ants as a computational intelligence technique. IEEE Comput Intell Mag 2006; 1: 28-39.