Optimizing Epidemic Dissemination with Channel Characteristics Awareness Theofanis Kontos 1 , Evripidis Zaimidis 2 , Christos Anagnostopoulos 1 , Stathes Hadjiefthymiades 1 , Evangelos Zervas 3 1 National and Kapodistrian University of Athens; 2 Hellenic Open University, 3 Technological Educational Institute of Athens Abstract—Ad hoc networks such as Wireless Sensor Networks (WSN) are characterized by the scarcity of energy resources. Their intelligent design can extend their lifetime without compromising the operation of network nodes and the applications running on them. To this end we propose an adaptive epidemic scheme that helps reduce energy expenditure through intelligent tuning of the forwarding rate. Locally measured error rate and redundant communications drive the adaptation of the forwarding rate. The former trigger the increase and the latter the decrease of the said rate. Our objective is to reach an optimum value, at which effective infection with minimal energy expense takes place. Simulation results show that significant energy gains can be obtained through the proposed scheme. Keywords—Ad hoc networks, Wireless sensor networks I. INTRODUCTION Wireless sensor networks (WSN) consist of nodes with minimal resources in terms of transmission, computing power, bandwidth and storage. It is a common requirement that the information owned by nodes has to be shared by other nodes and in many cases (e.g., monitoring applications [24], [25]) it has to be delivered to as many nodes as possible. This can be achieved through established information dissemination schemes. Unconditional data flooding by all nodes to all their neighbors can serve this purpose but it results to excessive resource consumption [17], [18]. The epidemic information dissemination model means transmitting data in a probabilistic rather than deterministic manner [8], [13]. This leads to curtail redundant communication. Less energy and network resources are, spent in an attempt to disseminate information to a large percentage of network nodes [6]. We adopt the epidemic paradigm for information dissemination within a WSN and propose an extension scheme, in which the forwarding probability is dynamically tuned taking into account (i) the amount of the local redundant message exchanges and (ii) the error rate due to channel noise observed locally on each node. The aim of the extension scheme is the reduction of redundant, unnecessary transmissions, while the forwarding rate can be increased at the presence of noise, in order to secure a more effective communication. The bottom line is to achieve efficient information dissemination at a lower energy cost, thus, rationalizing resource use. The structure of the paper is as follows: in section II we report concepts in epidemic dissemination and the rationale of our proposal. In section III significant previous work on the issue of adaptive epidemic schemes is presented. Section IV provides analysis of our scheme. Models for the network and the wireless channel are also elaborated upon in this section. Additionally, the proposed model is presented in detail. Section V shows performance metrics for evaluating the model as well as simulation results. Finally, conclusions and future work are discussed in section VI. II. RATIONALE Epidemic-based information dissemination is a well known paradigm for disseminating information in ad hoc wireless networks [1]. It guarantees the reception of pieces of information by as many network nodes as possible by “infecting” them in a probabilistic rather than deterministic manner. This is achieved with a given forwarding probability   (0, 1] (a.k.a. infection rate). Nodes that do not carry information are assumed to be in the susceptible state, whereas those that do are in the infected state. The cure of an infected node can occur at some time once the carried (infecting) piece of information turns obsolete or unusable. This can occur at a cure rate   [0, 1], i.e. an infected node can ‘infect’ other neighboring nodes, but can also be cured We define the effective cost in information dissemination for a certain model as the number of message exchanges in unit time over the percentage of infected nodes (or delivery rate). The probabilistic nature of the epidemic scheme reduces redundant transmissions [6] and the forwarding rate,  is the key parameter that we adjust in our scheme, in order to improve the information dissemination efficiency. We adopt the Susceptible-Infected-Susceptible (SIS) model [1]. In this paradigm, node infection (transition from the susceptible to the infected state) occurs at a rate  and the cure (the reverse transition) occurs at a rate . This means that a cured node can be re-infected and is in either the susceptible (S) or the infected (I) state before or after an infection, respectively. To be more precise, in our scheme we consider an error probability due to the wireless channel noise. This renders some infection attempts unsuccessful. Hence, the actual infection rate would be the forwarding rate  multiplied by this error probability, which is a value lower than .