Opportunistic Routing in Wireless Networks

Wireless multi-hop networks have become an important part of many modern communication systems. Opportunistic routing aims to overcome the deficiencies of conventional routing on wireless multi-hop networks, by specifically utilizing wireless broadcast opportunities and receiver diversity. Opportunistic routing algorithms, which are specifically optimized to incorporate into the routing decisions a model of wireless transmission, take advantage of scheduling, multi-user, andreceiver diversity gains and result in significant reduction in the expected cost of routing per packet. The ability of the algorithm to take advantage of the aspects of wireless transmission, however, depends on the scalability and the additional overhead associated with the opportunistic routing as well as the availability of side information regarding wireless channel statistics, topology, etc. This monograph sheds light on the performance gains associated with incorporating into the routing strategy the nature of wireless transmission.This monograph first provides an overview of various opportunistic distance-vector algorithms that have been developed to incorporate wireless transmission and routing opportunities. Furthermore, an optimal opportunistic distance metric is proposed whose performance is examined against the performance of several routing algorithms from the literature. The performance is examined first in analytical examples, then via simulation to identify the strengths of the optimal opportunist routing algorithm. To allow for a scalable and distributed solution, the distributed computation of this optimal distance-metric is provided. The performance of a distributed implementation of the optimal opportunistic routing algorithm is also examined via simulation. In addition to the construction of the opportunistic schemes in centralized and distributed fashions, this monograph also addresses how learning the wireless medium can be efficiently incorporated in the structure of routing algorithm. Finally, this monograph examines the dynamic congestion-based distance metric and its performance against other congestion aware solutions in the literature.

[1]  T. Javidi,et al.  No Regret Routing for ad-hoc wireless networks , 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.

[2]  Tara Javidi,et al.  A general class of throughput optimal routing policies in multi-hop wireless networks , 2009 .

[3]  Dina Katabi,et al.  Zigzag decoding: combating hidden terminals in wireless networks , 2008, SIGCOMM '08.

[4]  John S. Baras,et al.  A Probabilistic Emergent Routing Algorithm for Mobile Ad Hoc Networks , 2003 .

[5]  Michael L. Littman,et al.  Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach , 1993, NIPS.

[6]  Michael J. Neely,et al.  Optimal Backpressure Routing for Wireless Networks with Multi-Receiver Diversity , 2006, 2006 40th Annual Conference on Information Sciences and Systems.

[7]  Dimitri P. Bertsekas,et al.  Data Networks , 1986 .

[8]  James R. Zeidler,et al.  A delay-minimizing routing strategy for wireless multi-hop networks , 2009, 2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks.

[9]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[10]  Bhaskar Krishnamachari,et al.  LIFO-Backpressure Achieves Near-Optimal Utility-Delay Tradeoff , 2010, IEEE/ACM Transactions on Networking.

[11]  Aman Shaikh,et al.  Routing stability in congested networks: experimentation and analysis , 2000 .

[12]  Saikat Ray,et al.  Arbitrary Throughput Versus Complexity Tradeoffs in Wireless Networks Using Graph Partitioning , 2008, IEEE Transactions on Automatic Control.

[13]  Samir Ranjan Das,et al.  Exploiting path diversity in the link layer in wireless ad hoc networks , 2005, Sixth IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks.

[14]  John N. Tsitsiklis,et al.  Asynchronous stochastic approximation and Q-learning , 1994, Mach. Learn..

[15]  Abhijeet Bhorkar,et al.  Exploring and exploiting routing opportunities in wireless ad-hoc networks , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[16]  Lei Ying,et al.  On throughput optimality with delayed network-state information , 2008 .

[17]  John S. Baras,et al.  Convergence results for ant routing algorithms via stochastic approximation and optimization , 2010, 2007 46th IEEE Conference on Decision and Control.

[18]  Demosthenis Teneketzis,et al.  Stochastic routing in ad hoc wireless networks , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[19]  Robert Tappan Morris,et al.  a high-throughput path metric for multi-hop wireless routing , 2005, Wirel. Networks.

[20]  G. van Dooren,et al.  Introduction to radio propagation for fixed and mobile communications , 1999, IEEE Antennas and Propagation Magazine.

[21]  Robert Tappan Morris,et al.  ExOR: opportunistic multi-hop routing for wireless networks , 2005, SIGCOMM '05.

[22]  Demosthenis Teneketzis,et al.  Stochastic routing in ad-hoc networks , 2006, IEEE Transactions on Automatic Control.

[23]  Aarnout Brombacher,et al.  Probability... , 2009, Qual. Reliab. Eng. Int..

[24]  Dimitri Bertsekas,et al.  Distributed dynamic programming , 1981, 1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[25]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[26]  Robert Tappan Morris,et al.  Architecture and evaluation of an unplanned 802.11b mesh network , 2005, MobiCom '05.

[27]  I Chih-Lin,et al.  Wireless Communications and Networks , 2004 .

[28]  Shailesh Kumar and Risto Miikkulainen.  Dual Reinforcement Q-Routing: An On-Line Adaptive Routing Algorithm , 1997 .

[29]  Elizabeth M. Belding-Royer,et al.  A review of current routing protocols for ad hoc mobile wireless networks , 1999, IEEE Wirel. Commun..

[30]  Anatolij Zubow,et al.  Cooperative Opportunistic Routing Using Transmit Diversity in Wireless Mesh Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[31]  Dit-Yan Yeung,et al.  Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control , 1995, NIPS.

[32]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Vol. II , 1976 .

[33]  Ran Liu,et al.  Enhancing the Delay Performance of Dynamic Backpressure Algorithms , 2016, IEEE/ACM Trans. Netw..

[34]  Jeffrey M. Jaffe,et al.  A Responsive Distributed Routing Algorithm for Computer Networks , 1982, ICDCS.

[35]  Marco Ajmone Marsan,et al.  Optimal Scheduling and Routing for Maximum Network Throughput , 2007, IEEE/ACM Transactions on Networking.

[36]  E. Yeh,et al.  Throughput Optimal Distributed Control of Stochastic Wireless Networks , 2006, 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks.

[37]  S. Resnick.  A Probability Path , 1999 .

[38]  Babak Hassibi,et al.  Wireless erasure networks with feedback , 2008, 2008 IEEE International Symposium on Information Theory.

[39]  T. Javidi,et al.  Towards Throughput and Delay Optimal Routing for Wireless Ad-Hoc Networks , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

[40]  Lei Ying,et al.  On Combining Shortest-Path and Back-Pressure Routing Over Multihop Wireless Networks , 2009, IEEE INFOCOM 2009.

[41]  Martin L. Puterman,et al.  Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .

[42]  Tara Javidi,et al.  Opportunistic routing under unknown stochastic models , 2013, 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

[43]  Eytan Modiano,et al.  Dynamic power allocation and routing for time varying wireless networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[44]  Sanjay Shakkottai,et al.  Hop-by-Hop Congestion Control Over a Wireless Multi-Hop Network , 2004, IEEE/ACM Transactions on Networking.

[45]  Peter Larsson.  Selection diversity forwarding in a multihop packet radio network with fading channel and capture , 2001, MobiHoc '01.

[46]  Stuart J. Russell,et al.  Reinforcement Learning with Hierarchies of Machines , 1997, NIPS.

[47]  Uyless D. Black,et al.  IP Routing Protocols: RIP, OSPF, BGP, PNNI and Cisco Routing Protocols , 2000 .

[48]  Piet Van Mieghem,et al.  Responsible Editor: A. Kshemkalyani , 2006 .

[49]  Michele Zorzi,et al.  Geographic Random Forwarding (GeRaF) for Ad Hoc and Sensor Networks: Multihop Performance , 2003, IEEE Trans. Mob. Comput..

[50]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1990, 29th IEEE Conference on Decision and Control.