Generalized Cooperative Multicast in Mobile Ad Hoc Networks

Cooperative multicast serves as an efficient communication paradigm for supporting multicast-intensive applications in mobile ad hoc networks (MANETs). Available studies on cooperative multicast in MANETs mainly focus on either the full cooperation or the noncooperation, which fail to capture the more general cooperation behaviors among destination nodes. To address this issue, this paper proposes a general cooperative multicast scheme CM(<inline-formula> <tex-math notation="LaTeX">$f,g, p,\tau$</tex-math></inline-formula>) with replication factor <inline-formula> <tex-math notation="LaTeX">$f$</tex-math></inline-formula>, multicast fanout <inline-formula><tex-math notation="LaTeX"> $g$</tex-math></inline-formula>, cooperative probability <inline-formula><tex-math notation="LaTeX">$p$</tex-math> </inline-formula>, and packet lifetime <inline-formula><tex-math notation="LaTeX">$\tau$</tex-math></inline-formula>. With this scheme, a packet from source node will be replicated to at most <inline-formula><tex-math notation="LaTeX"> $f$</tex-math></inline-formula> distinct relay nodes, which forward the packet to its <inline-formula> <tex-math notation="LaTeX">$g$</tex-math></inline-formula> destination nodes, and with probability <inline-formula> <tex-math notation="LaTeX">$p$</tex-math></inline-formula> a destination node helps to forward the packet. Here, the packet has the lifetime of <inline-formula><tex-math notation="LaTeX">$\tau$</tex-math></inline-formula> time slots. The scheme is flexible and general, and it covers the full cooperation (<inline-formula><tex-math notation="LaTeX">$p = 1$</tex-math></inline-formula>) and the noncooperation (<inline-formula><tex-math notation="LaTeX">$p = 0$</tex-math> </inline-formula>) as special cases. A Markov chain theoretical model is further developed to depict the packet delivery process under the new scheme and help us to conduct analytical study on the corresponding expected packet delivery probability and packet delivery cost. Finally, extensive simulation and numerical results are provided for discussions.

[1]  Emina Soljanin,et al.  Coding Improves the Throughput-Delay Tradeoff in Mobile Wireless Networks , 2012, IEEE Trans. Inf. Theory.

[2]  Michael J. Neely,et al.  Dynamic power allocation and routing for satellite and wireless networks with time varying channels , 2003 .

[3]  Yujie Han,et al.  5G Converged Cell-Less Communications in Smart Cities , 2016, IEEE Communications Magazine.

[4]  Xinbing Wang,et al.  MotionCast: on the capacity and delay tradeoffs , 2009, MobiHoc '09.

[5]  Cheng-Xiang Wang,et al.  5G Ultra-Dense Cellular Networks , 2015, IEEE Wireless Communications.

[6]  Xinbing Wang,et al.  Speed Improves Delay-Capacity Trade-Off in MotionCast , 2011, IEEE Transactions on Parallel and Distributed Systems.

[7]  Xiaohong Jiang,et al.  Multicast capacity, delay and delay jitter in intermittently connected mobile networks , 2012, 2012 Proceedings IEEE INFOCOM.

[8]  Feng Yang,et al.  On Multicast Capacity and Delay in Cognitive Radio Mobile Ad Hoc Networks , 2015, IEEE Transactions on Wireless Communications.

[9]  Yuguang Fang,et al.  Throughput, Delay, and Mobility in Wireless Ad Hoc Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[10]  Yuguang Fang,et al.  On the improvement of scaling laws for large-scale MANETs with network coding , 2009, IEEE Journal on Selected Areas in Communications.

[11]  Jaehoon Jeong,et al.  TMA: Trajectory-based Multi-Anycast forwarding for efficient multicast data delivery in vehicular networks , 2013, Comput. Networks.

[12]  Yuguang Fang,et al.  On the Throughput Capacity of Heterogeneous Wireless Networks , 2012, IEEE Transactions on Mobile Computing.

[13]  Sanjeev R. Kulkarni,et al.  A deterministic approach to throughput scaling in wireless networks , 2002, IEEE Transactions on Information Theory.

[14]  Song Guo,et al.  A Game Theoretic Approach to Parked Vehicle Assisted Content Delivery in Vehicular Ad Hoc Networks , 2017, IEEE Transactions on Vehicular Technology.

[15]  Xiaohong Jiang,et al.  Delay and Capacity in Ad Hoc Mobile Networks with f-cast Relay Algorithms , 2011, IEEE Transactions on Wireless Communications.

[16]  Xiang-Yang Li,et al.  Multicast capacity scaling for inhomogeneous mobile ad hoc networks , 2013, Ad Hoc Networks.

[17]  Panganamala Ramana Kumar,et al.  RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN , 2001 .

[18]  Yuguang Fang,et al.  Smooth Trade-Offs between Throughput and Delay in Mobile Ad Hoc Networks , 2012, IEEE Transactions on Mobile Computing.

[19]  Xiaohu Ge,et al.  Energy Efficiency Challenges of 5G Small Cell Networks , 2017, IEEE Communications Magazine.

[20]  Xinbing Wang,et al.  Delay and Capacity Tradeoff Analysis for MotionCast , 2011, IEEE/ACM Transactions on Networking.

[21]  David Tse,et al.  Mobility increases the capacity of ad-hoc wireless networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[22]  R. Srikant,et al.  The multicast capacity of large multihop wireless networks , 2010, TNET.

[23]  Xiaohong Jiang,et al.  On the exact multicast delay in mobile ad hoc networks with f-cast relay , 2015, Ad Hoc Networks.

[24]  Xi Chen,et al.  Multicast Capacity in MANET with Infrastructure Support , 2014, IEEE Transactions on Parallel and Distributed Systems.

[25]  Xinbing Wang,et al.  Optimal Multicast Capacity and DelayTradeoffs in MANETs , 2014, IEEE Trans. Mob. Comput..

[26]  Eytan Modiano,et al.  Capacity and delay tradeoffs for ad hoc mobile networks , 2005, IEEE Trans. Inf. Theory.

[27]  Yin Chen,et al.  Throughput analysis in mobile ad hoc networks with directional antennas , 2013, Ad Hoc Networks.

[28]  Massimo Franceschetti,et al.  Closing the Gap in the Capacity of Wireless Networks Via Percolation Theory , 2007, IEEE Transactions on Information Theory.

[29]  Xinbing Wang,et al.  Cooperation Achieves Optimal Multicast Capacity-Delay Scaling in MANET , 2012, IEEE Transactions on Communications.

[30]  Devavrat Shah,et al.  Optimal throughput-delay scaling in wireless networks - part I: the fluid model , 2006, IEEE Transactions on Information Theory.