On the Throughput and Delay in Ad Hoc Networks With Human Mobility

In this paper, we study the impact of human mobility on throughput and delay for people-centric applications in mobile ad hoc networks (MANETs). We consider a general human mobility model for MANETs, which can capture important features of human mobility, such as time correlation, node correlation, location heterogeneity, and node heterogeneity. Multiple unicasts with general arrival processes are delivered, and nodes are equipped with infinite buffers. Under our system model, we first characterize the network stability region in terms of the probability of each node set visiting each location and the amount of transmission resources at each location. We show that the node correlation and heterogeneity of locations' popularity usually decrease the size of the network stability region, whereas the diversity of locations visited by a node usually increases the size of the network stability region. Then, by solving a stability-related optimization problem, we develop a throughput-optimal policy based on the obtained optimal solution. We obtain the upper and lower bounds of the delay performance under the proposed policy. Finally, using simulations based on a theoretical model and some real traces, we verify the analytical results and compare the performance of the proposed policy with some existing policies.

[1]  Paolo Giaccone,et al.  On the Capacity Region of MANET: Scheduling and Routing Strategy , 2009, IEEE Transactions on Vehicular Technology.

[2]  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).

[3]  Suhas N. Diggavi,et al.  Even One-Dimensional Mobility Increases the Capacity of Wireless Networks , 2005, IEEE Transactions on Information Theory.

[4]  Charles X. Ling,et al.  A Reliable People Counting System via Multiple Cameras , 2012, TIST.

[5]  Ness B. Shroff,et al.  Degenerate delay-capacity tradeoffs in ad-hoc networks with Brownian mobility , 2006, IEEE Transactions on Information Theory.

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

[7]  Devavrat Shah,et al.  Throughput and Delay in Random Wireless Networks With Restricted Mobility , 2007, IEEE Transactions on Information Theory.

[8]  Pan Hui,et al.  Pocket switched networks and human mobility in conference environments , 2005, WDTN '05.

[9]  Marco Conti,et al.  Mobile ad hoc networking: milestones, challenges, and new research directions , 2014, IEEE Communications Magazine.

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

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

[12]  Evangelos D. Spyrou,et al.  Using social network theory for modeling human mobility , 2010, IEEE Network.

[13]  Christophe Diot,et al.  Impact of Human Mobility on Opportunistic Forwarding Algorithms , 2007, IEEE Transactions on Mobile Computing.

[14]  Leandros Tassiulas,et al.  Resource Allocation and Cross Layer Control in Wireless Networks (Foundations and Trends in Networking, V. 1, No. 1) , 2006 .

[15]  Kyunghan Lee,et al.  On the Levy-Walk Nature of Human Mobility , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[16]  Thomas F. La Porta,et al.  On Exploiting Transient Social Contact Patterns for Data Forwarding in Delay-Tolerant Networks , 2013, IEEE Transactions on Mobile Computing.

[17]  Eytan Modiano,et al.  Erratum to "Capacity and Delay Tradeoffs for Ad Hoc Mobile Networks" , 2005, IEEE Transactions on Information Theory.

[18]  Michele Garetto,et al.  Impact of Correlated Mobility on Delay–Throughput Performance in Mobile Ad Hoc Networks , 2011, IEEE/ACM Transactions on Networking.

[19]  Ying Zhu,et al.  A Survey of Social-Based Routing in Delay Tolerant Networks: Positive and Negative Social Effects , 2013, IEEE Communications Surveys & Tutorials.

[20]  Pan Hui,et al.  BUBBLE Rap: Social-Based Forwarding in Delay-Tolerant Networks , 2011 .

[21]  Dino Pedreschi,et al.  Human mobility, social ties, and link prediction , 2011, KDD.

[22]  Chaoming Song,et al.  Modelling the scaling properties of human mobility , 2010, 1010.0436.

[23]  Shaojie Tang,et al.  COUPON: A Cooperative Framework for Building Sensing Maps in Mobile Opportunistic Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

[24]  Leandros Tassiulas,et al.  Resource Allocation and Cross-Layer Control in Wireless Networks , 2006, Found. Trends Netw..

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

[26]  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).

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