An Adaptive Method for Dynamic Audience Size Estimation in Multicast

Nekovee, Maziar; Soppera, Andrea; Burbridge, Trevor

doi:10.1007/978-3-540-39405-1_3

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…A typical approach is to sample some property of the system which is random but depends on network size and so can be used to apply maximum likelihood estimation or a similar technique. This approach was followed in [20] in the context of multicasting. Another, probabilistic and localized technique is described in [9] where a logical ring is maintained and all nodes estimate network size locally based on the estimates of their neighbors.…”

Section: Related Workmentioning

confidence: 99%

Gossip-based aggregation in large dynamic networks

Jelasity

Montresor

Babaoğlu

2005

ACM Trans. Comput. Syst.

585

603

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As computer networks increase in size, become more heterogeneous and span greater geographic distances, applications must be designed to cope with the very large scale, poor reliability, and often, with the extreme dynamism of the underlying network. Aggregation is a key functional building block for such applications: it refers to a set of functions that provide components of a distributed system access to global information including network size, average load, average uptime, location and description of hotspots, etc. Local access to global information is often very useful, if not indispensable for building applications that are robust and adaptive. For example, in an industrial control application, some aggregate value reaching a threshold may trigger the execution of certain actions; a distributed storage system will want to know the total available free space; load balancing protocols may benefit from knowing the target average load so as to minimize the load they transfer. We propose a gossip-based protocol for computing aggregate values over network components in a fully decentralized fashion. The class of aggregate functions we can compute is very broad and includes many useful special cases such as counting, averages, sums, products and extremal values. The protocol is suitable for extremely large and highly dynamic systems due to its proactive structure-all nodes receive the aggregate value continuously, thus being able to track any changes in the system. The protocol is also extremely lightweight making it suitable for many distributed applications including peer-to-peer and grid computing systems. We demonstrate the efficiency and robustness of our gossip-based protocol both theoretically and experimentally under a variety of scenarios including node and communication failures.

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Section: Related Workmentioning

confidence: 99%

Gossip-based aggregation in large dynamic networks

Jelasity

Montresor

Babaoğlu

2005

ACM Trans. Comput. Syst.

585

603

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“…10: return est nodes // the estimation of the number of nodes tree [19], [10]. The same problem has been addressed by researchers in data communications with the goal of estimating the size of the audience of a multicast communication [6], [13]. Anyway, all previous algorithms assume the presence of spatial decoupling, hence the parallelization of the communication.…”

Section: B Previous Work On Countmentioning

confidence: 99%

How many are you (an approach for the smart dust world)?

Albano

Pereira

Tovar

2013

2013 IEEE 1st International Conference on Cyber-Physical Systems, Networks, and Applications (CPSNA)

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As the size and cost of embedded devices continue to decrease, it becomes economically feasible to densely deploy networks with very large quantities of such nodes, and thus enabling the implementation of networks with increasingly larger number of nodes becomes a relevant problem. In this paper we describe a novel algorithm to obtain the number of live nodes with a very low time-complexity. In particular, we develop a mechanism to estimate the number of nodes or the number of proposed values (COUNT), with a time complexity that increases sublinearly with the number of nodes. The approach we propose is based on the wise exploitation of dominance-based protocols and offers excellent scalability properties for emerging applications in dense Cyber Physical Systems.

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