Timely dissemination of information to mobile users is vital in many applications. In a critical situation, no network infrastructure may be available for use in dissemination, over and above the on-board storage capability of the mobile users themselves. We consider the following specialized content distribution application: a group of users equipped with wireless devices build an ad hoc network in order cooperatively to retrieve information from certain regions (the mission sites). Each user requires access to some set of information items originating from sources lying within a region. Each user desires low-latency access to its desired data items, upon request (i.e., when pulled). In order to minimize average response time, we allow users to pull data either directly from sources or, when possible, from other nearby users who have already pulled, and continue to carry, the desired data items. That is, we allow for data to be pushed to one user and then pulled by one or more additional users. The total latency experienced by a user vis-vis a certain data item is then in general a combination of the push delay and the pull delay. We assume each delay time is a function of the hop distance between the pair of points in question. Our goal in this paper is to assign data to mobile users, in order to minimize the total cost and the average latency experienced by all the users. In a static setting, we solve this problem in two different schemes, one of which is easy to solve but wasteful, one of which relates to NP-hard problems but is less so. Then in a dynamic setting, we adapt the algorithm for the static setting and develop a new algorithm with respect to users' gradual arrival. In the end we show a trade-off can be made between minimizing the cost and latency.
[1]
Albert,et al.
Emergence of scaling in random networks
,
1999,
Science.
[2]
Deborah Estrin,et al.
Directed diffusion: a scalable and robust communication paradigm for sensor networks
,
2000,
MobiCom '00.
[3]
David S. Johnson,et al.
Computers and Intractability: A Guide to the Theory of NP-Completeness
,
1978
.
[4]
Shervin Shirmohammadi,et al.
A survey of application-layer multicast protocols
,
2007,
IEEE Communications Surveys & Tutorials.
[5]
Stephen E. Deering,et al.
Multicast routing in datagram internetworks and extended LANs
,
1990,
TOCS.
[6]
Alex Zelikovsky,et al.
Tighter Bounds for Graph Steiner Tree Approximation
,
2005,
SIAM J. Discret. Math..
[7]
Hans Kellerer,et al.
Knapsack problems
,
2004
.
[8]
Vijay V. Vazirani,et al.
Approximation Algorithms
,
2001,
Springer Berlin Heidelberg.
[9]
Thomas F. La Porta,et al.
Proactive Data Dissemination to Mission Sites
,
2009,
2009 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.
[10]
Deborah Estrin,et al.
GHT: a geographic hash table for data-centric storage
,
2002,
WSNA '02.
[11]
Diomidis Spinellis,et al.
A survey of peer-to-peer content distribution technologies
,
2004,
CSUR.