On real-time capacity of event-driven data-gathering sensor networks

Network capacity is a critical feature of wireless ad hoc and sensor networks. It is particularly challenging to determine network capacity when combined with other performance objectives such as timeliness. This paper investigates real-time capacity for event-driven data-gathering sensor networks with the unbalanced many-to-one traffic pattern. First, we compute the average allowable throughputs of nodes for a given event distribution, based on which we then leverage results of queuing theory to estimate the per-hop delays. We develop a new slack time distribution scheme for the unbalanced many-to-one traffic pattern, and prove it optimal in terms of the per-hop success probability. Here the per-hop success probability is defined as the probability for a packet to meet its sub-deadlines at each hop. Finally, we define the network-wide real-time capacity, i.e., given a threshold for the per-hop success probability, how much data (in bit per second) can be delivered to the sink node meeting their deadlines. For these research results, we provide some application scenarios, including configuring packet deadlines or verifying a specific deadline configuration, setting a packet's priority for dynamic scheduling, and trading the reliability of real-time data delivery for capacity efficiency etc. We also study two special cases of WSNs, the chain model and the continuous model. Our slack distribution scheme yields consistent or similar results for these two special cases as that of past works, but is more adaptive by supporting more generic cases.

[1]  Gerhard Kramer,et al.  Hierarchical sensor networks: capacity bounds and cooperative strategies using the multiple-access relay channel model , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[2]  Michael Gastpar,et al.  On the capacity of wireless networks: the relay case , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[3]  Zhen Liu,et al.  Capacity, delay and mobility in wireless ad-hoc networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

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

[5]  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).

[6]  Prasant Mohapatra,et al.  Power conservation and quality of surveillance in target tracking sensor networks , 2004, MobiCom '04.

[7]  Damla Turgut,et al.  Congestion Avoidance and Fairness in Wireless Sensor Networks , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[8]  M. Vetterli,et al.  Lattice sensor networks: capacity limits, optimal routing and robustness to failures , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[9]  Mor Harchol-Balter,et al.  In Network of Queues, M/M/1 Can Outperform M/D/1 , 1994 .

[10]  Özgür B. Akan,et al.  A real-time and reliable transport (RT) 2 protocol for wireless sensor and actor networks , 2008, IEEE/ACM Trans. Netw..

[11]  P. Kumar,et al.  Capacity of Ad Hoc Wireless Networks , 2002 .

[12]  Timo Hämäläinen,et al.  Cost-Aware Capacity Optimization in Dynamic Multi-Hop WSNs , 2007, 2007 Design, Automation & Test in Europe Conference & Exhibition.

[13]  Panganamala Ramana Kumar,et al.  Computing and communicating functions over sensor networks , 2005, IEEE Journal on Selected Areas in Communications.

[14]  Lili Qiu,et al.  Impact of Interference on Multi-Hop Wireless Network Performance , 2003, MobiCom '03.

[15]  Panganamala Ramana Kumar,et al.  Toward a theory of in-network computation in wireless sensor networks , 2006, IEEE Communications Magazine.

[16]  Nael B. Abu-Ghazaleh,et al.  A taxonomy of wireless micro-sensor network models , 2002, MOCO.

[17]  Hesham El Gamal.  On the scaling laws of dense wireless sensor networks: the data gathering channel , 2005, IEEE Trans. Inf. Theory.

[18]  Tarek F. Abdelzaher,et al.  On real-time capacity limits of multihop wireless sensor networks , 2004, 25th IEEE International Real-Time Systems Symposium.

[19]  Mingyan Liu,et al.  Data-gathering wireless sensor networks: organization and capacity , 2003, Comput. Networks.

[20]  H. Vincent Poor,et al.  On the capacity of mobile ad hoc networks with delay constraints , 2006, IEEE Transactions on Wireless Communications.

[21]  Kiseon Kim,et al.  Interference and Sink Capacity of Wireless CDMA Sensor Networks with Layered Architecture , 2008 .

[22]  Gautam H. Thaker,et al.  A feasible region for meeting aperiodic end-to-end deadlines in resource pipelines , 2004, 24th International Conference on Distributed Computing Systems, 2004. Proceedings..

[23]  Mingyan Liu,et al.  On the Many-to-One Transport Capacity of a Dense Wireless Sensor Network and the Compressibility of Its Data , 2003, IPSN.

[24]  Donald F. Towsley,et al.  On the capacity of hybrid wireless networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[25]  Erik D. Demaine,et al.  Deploying sensor networks with guaranteed capacity and fault tolerance , 2005, MobiHoc '05.

[26]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.