Achieving True Video-on-Demand Service in Multi-Hop WiMax Mesh Networks

In this work, we discuss how to support video-on-demand service in multi-hop WiMax mesh networks. We are interested in the scenario that end users connect to the video servers through the base station of the multi-hop WiMax networks. We propose a model that can jointly solve the admission control and channel scheduling problems. Our proposed approach guarantees the required data rate is achieved for video streams, which is crucial for multimedia streaming applications. An efficient multicast routing technique is also proposed to minimize the bandwidth cost of joining a multicast tree. Furthermore, we adopt the application layer patching technique to accommodate end users that join a video multicast group at different times. Overall, our solution efficiently utilizes the bandwidth resource of the networks and provides data rate guarantee for video streams. Simulation study shows that with the proposed approach, true video-on-demand in WiMax mesh networks can be achieved under high video request arrival rate.

[1]  Qian Guo,et al.  An integrated QoS control architecture for IEEE 802.16 broadband wireless access systems , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[2]  Pedro M. Ruiz,et al.  Efficient multicast routing in wireless mesh networks connected to internet , 2006, InterSense '06.

[3]  Hung-Yu Wei,et al.  On Admission of VoIP Calls Over Wireless Mesh Network , 2006, 2006 IEEE International Conference on Communications.

[4]  Min Cao,et al.  A tractable algorithm for fair and efficient uplink scheduling of multi-hop wimax mesh networks , 2006, 2006 2nd IEEE Workshop on Wireless Mesh Networks.

[5]  Dina Katabi,et al.  A framework for scalable global IP-anycast (GIA) , 2000, SIGCOMM 2000.

[6]  Koen Langendoen,et al.  Murphy loves potatoes: experiences from a pilot sensor network deployment in precision agriculture , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[7]  Edith Cohen,et al.  Replication strategies in unstructured peer-to-peer networks , 2002, SIGCOMM.

[8]  Christos H. Papadimitriou,et al.  Selfish caching in distributed systems: a game-theoretic analysis , 2004, PODC '04.

[9]  Mani Srivastava,et al.  Energy-aware wireless microsensor networks , 2002, IEEE Signal Process. Mag..

[10]  Hui Zhang,et al.  Predicting Internet network distance with coordinates-based approaches , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[11]  Michael Mitzenmacher,et al.  The Power of Two Choices in Randomized Load Balancing , 2001, IEEE Trans. Parallel Distributed Syst..

[12]  David R. Karger,et al.  Consistent hashing and random trees: distributed caching protocols for relieving hot spots on the World Wide Web , 1997, STOC '97.

[13]  Jim Davies,et al.  A Comparison of Replication Strategies for Reliable Decentralised Storage , 2006, J. Networks.

[14]  Vinod Sharma,et al.  Algorithms for routing and centralized scheduling to provide QoS in IEEE 802.16 mesh networks , 2005, WMuNeP '05.

[15]  Muneeb Ali,et al.  Protothreads: simplifying event-driven programming of memory-constrained embedded systems , 2006, SenSys '06.

[16]  Dimitrios Tsoumakos,et al.  APRE: A Replication Method for Unstructured P2P Networks , 2006 .

[17]  Suman Banerjee,et al.  VoIP on Wireless Meshes: Models, Algorithms and Evaluation , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[18]  Rolf Winter,et al.  ScatterWeb - Low Power Sensor Nodes and Energy Aware Routing , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[19]  Wei Yu,et al.  A Cross-Layer Optimization Framework for Multihop Multicast in Wireless Mesh Networks , 2006, IEEE Journal on Selected Areas in Communications.

[20]  Vinayak S. Naik,et al.  A line in the sand: a wireless sensor network for target detection, classification, and tracking , 2004, Comput. Networks.

[21]  Ying Cai,et al.  Optimizing patching performance , 1998, Electronic Imaging.

[22]  Adam Dunkels,et al.  Software-based on-line energy estimation for sensor nodes , 2007, EmNets '07.

[23]  Mark D. Yarvis,et al.  Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north sea , 2005, SenSys '05.

[24]  Marcel Waldvogel,et al.  Routing and Data Location in Overlay Peer-to-Peer Networks , 2002 .

[25]  T. V. Lakshman,et al.  Source models for VBR broadcast-video traffic , 1996, TNET.

[26]  Adam Dunkels,et al.  Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[27]  Chen-Nee Chuah,et al.  Error resilient concurrent video streaming over wireless mesh networks , 2006 .

[28]  P. Baldi,et al.  Software Acoustic Modems for Short Range Mote-based Underwater Sensor Networks , 2006, OCEANS 2006 - Asia Pacific.

[29]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[30]  Richard M. Karp,et al.  Probabilistic recurrence relations , 1994, JACM.

[31]  Marcel Waldvogel,et al.  Dynamic Replica Management in Distributed Hash Tables , 2003 .

[32]  Dimitrios Koutsonikolas,et al.  High-throughput multicast routing metrics in wireless mesh networks , 2008, Ad Hoc Networks.

[33]  Yuan Li,et al.  Research challenges and applications for underwater sensor networking , 2006, IEEE Wireless Communications and Networking Conference, 2006. WCNC 2006..

[34]  Lixin Gao,et al.  Optimal Patching Schemes for Efficient Multimedia Streaming , 1999 .

[35]  Douglas M. Blough,et al.  The Effect of Replica Placement on Routing Robustness in Distributed Hash Tables , 2006, Sixth IEEE International Conference on Peer-to-Peer Computing (P2P'06).