The Role of Location Popularity in Multicast Mobile Ad Hoc Networks

In the asymptotic analysis of large scale mobile networks, most previous works assume that nodes move in all the cells identically. We put forward this line of research by considering location popularity, which is verified by recent experimental studies. Nodes tend to visit some popular locations and go to other locations less frequently. We first analyze its multicast capacity and delay under the traditional 2-hop store-carry and forward paradigm. With different location popularity distributions, network capacity and delay will vary according to the distribution exponent. As the popularity becomes more diverse, less concurrent transmissions are tolerated in the network, which brings down the performance. Observing that transmission opportunity is not fully utilized in popular cells for 2-hop paradigm, we put forward a 3-hop scheme, which is called store-carry-accelerate-forward scheme. In this 3-hop scheme, each packet is first sent to an initial relay, who carries the packets into the popular cells and then broadcasts to multiple nodes to accelerate the delivery. By so doing, we showed that the 3-hop scheme outperforms the 2-hop scheme for all popularity distributions. Furthermore, we study the delay-capacity tradeoffs for multicast under both schemes and the buffer needed for stability requirement. Our results reveals the joint impact of multicast and location heterogeneity on the design of transmission schemes, and may shed new insights for future studies.

[1]  Ness B. Shroff,et al.  The Fundamental Capacity-Delay Tradeoff in Large Mobile Wireless Networks , .

[2]  Eytan Modiano,et al.  Dynamic power allocation and routing for time-varying wireless networks , 2005 .

[3]  Xinbing Wang,et al.  Impact of Location Popularity on Throughput and Delay in Mobile Ad Hoc Networks , 2015, IEEE Transactions on Mobile Computing.

[4]  Xiang-Yang Li.  Multicast capacity of wireless ad hoc networks , 2009, TNET.

[5]  Hamid R. Sadjadpour,et al.  Multicast Throughput Order of Network Coding in Wireless Ad-hoc Networks , 2009, 2009 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

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

[7]  Lei Ying,et al.  On Delay Constrained Multicast Capacity of Large-Scale Mobile Ad-Hoc Networks , 2009, 2010 Proceedings IEEE INFOCOM.

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

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

[10]  Albert-László Barabási,et al.  Understanding individual human mobility patterns , 2008, Nature.

[11]  Shaojie Tang,et al.  Multicast Capacity Scaling Laws for Multihop Cognitive Networks , 2012, IEEE Transactions on Mobile Computing.

[12]  Xinbing Wang,et al.  Capacity Scaling in Mobile Wireless Ad Hoc Network with Infrastructure Support , 2010, 2010 IEEE 30th International Conference on Distributed Computing Systems.

[13]  Yuguang Fang,et al.  The Capacity of Heterogeneous Wireless Networks , 2010, 2010 Proceedings IEEE INFOCOM.

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

[15]  Dino Pedreschi,et al.  Understanding the patterns of car travel , 2013 .

[16]  Muhammad Aamir,et al.  A Buffer Management Scheme for Packet Queues in MANET , 2013 .

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

[18]  Michele Garetto,et al.  Restricted Mobility Improves Delay-Throughput Tradeoffs in Mobile Ad Hoc Networks , 2008, IEEE Transactions on Information Theory.

[19]  Injong Rhee,et al.  Revisiting delay-capacity tradeoffs for mobile networks: The delay is overestimated , 2012, 2012 Proceedings IEEE INFOCOM.

[20]  Albert-László Barabási,et al.  Modelling the scaling properties of human mobility , 2010, 1010.0436.

[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).