A naive approach to deliver query q to its relevant sensor nodes is to flood q into the network. In flooding, each sensor broadcasts query q to its neighbors when q is received. Apparently, in this approach, a node may and often does receive multiple copies of q. However, as a matter of fact, only one copy of q is needed at each sensor and all other copies are not needed. As a result, a large number of redundant transmissions are incurred during flooding [86]. Probabilistic approaches such as Gossip were initially proposed to resolve inconsistencies among database servers [87]. When a database is replicated at many sites, maintaining mutual consistency among the sites in the face of updates is a significant problem. It has been shown that deterministic algorithms for replicated database consistency can be replaced with simple randomized algorithms. In randomized approaches, a site randomly updates other sites during maintenance. The probability of inconsistency can be made arbitrarily small by carefully configuring the random updating process. This problem shares a lot of similarity with the routing request transmission in ad hoc networks and sensor networks.
In [88], Gossip is integrated with an ad hoc routing protocol to reduce the overhead of sending routing requests into nodes in the network. Several probabilistic schemes are presented to send routing requests to nodes in the network with high probability. In the basic approach, a node, upon receiving a routing request message, m, forwards m to its neighboring nodes with probability p. A very high probability that all nodes receive a copy of the broadcast message, m, can be achieved if p is sufficiently high. To prevent the early death of m, it is also suggested that the first several hops should always forward m to their neighboring nodes. Other more complex schemes adapting p to local information, such as the number of neighbors at sensor nodes, are also presented and discussed.
In the work described at [89], a Gossip-based broadcast scheme is investigated for het- erogenous and dynamic networks. In these networks, it is impossible to adjust the parameters of the Gossip algorithm off line. Instead, it must be dynamically adjusted to current network conditions. A node’s gossip rate is adjusted according to the resources available within other nodes in the network. This information, required to perform adaptation, is embedded in the
normal gossip of data messages and exchanged among nodes through these data messages. Global congestion information is used to control the message emission rate at nodes which want to transmit data.
The probability can be further adapted to each node’s coverage information in the net- work [90]. In such schemes, the contribution of each node to the broadcast of routing requests is quantified as coverage in terms of area, copies or number of neighbors. The for- warding probability is adapted to each node’s coverage contribution. The different values of forwarding probabilities at neighboring sensor nodes ideally lead to a small set of nodes forwarding routing requests at any time while ensuring that each routing request can reach its destination node with high probability. The effect of probabilistic forwarding on the route established is studied through simulations. Results show that transmissions of routing requests can be further reduced with only a slight increase in routing delay.
In [91], Gossip-based approaches are utilized for group-based reliable multicast in large scale distributed applications. A reliable probabilistic multicast scheme, rpbcast, is pre- sented. Rpbcast is a hybrid of centralized and gossip based approaches. It uses gossip as the primary retransmission mechanism and only contacts loggers if gossips fail. Rpbcast adds packet reliability guarantees to Gossip-based multicast using loggers, and in the meantime preserves the performance advantages of Gossip-based multicast. Large groups of active senders are supported using negative gossip that specifies those messages a receiver is miss- ing instead of those messages it has received. The negative gossip allows pull-based recovery, which converges faster than push-based recovery. Rpbcast also applies hashing techniques to reduce message overhead and approximate group membership for garbage collection.
The underlying assumptions of gossip are discussed in [92], as well as how sensitive the robustness of gossip is to these assumptions. A list of five hidden assumptions are stated ex- plicitly. Among them are “In a gossip protocol, participants gossip with one or more partners at fixed time intervals”; “There is a bound on how many updates are concurrently propa- gated” and “Every gossip interaction is independent of concurrent gossiping between other processes”. The authors also discussed briefly how to ensure the performance advantages of Gossip in different scenarios when these assumptions are not valid.
casting and routing [27][93][94][95]. In [27], a probabilistic routing algorithm, rumor routing, is presented to reduce the communication cost of delivering events to queries. In rumor rout- ing, when a sensor node observes an event, it probabilistically generates an agent to forward the event to its neighboring sensor nodes. Similarly, when a query is generated or received at a sensor node, the sensor node forwards the query in a random direction if it does not have a route to the event. By disseminating events probabilistically to other sensors in the network, a query may reach sensors along a route to the event with less number of hops. Rumor routing, however, is only useful when the number of queries compared to the number of events is not too large or too small. The parameters in rumor routing can be adjusted to support different query to event ratios, delivery rates and route repairs.
Parametric probabilistic sensor network routing protocols apply a limited flooding strat- egy during route discovery [93]. The key element is that the retransmission probability for a packet at a sensor node is a function of various parameters rather than a constant. For destination attractor, a sensor closer to the destination of a message forwards with a higher retransmission probability. In contrast, for directed transmission, a sensor in the shortest path towards the destination forwards with a very high probability. The global information needed by these two schemes, the hop distance to the destination and the distance from source to the destination is estimated using a light weight message exchange protocol. It has been shown through simulations that different quality of service levels, measured as a fraction of packets delivered, can be supported by destination attractors and directed transmission, even in the presence of highly noisy network information.
Localized techniques for broadcasting in multi-hop ad hoc sensor networks are discussed in [94]. The authors present three different schemes: the Irrigator protocol, the Irrigator v2.0 scheme and the Fireworks protocol. The first two schemes are based on the idea of flooding over a sparse virtual topology, computed by means of inexpensive and fully decentralized pro- tocols. The Fireworks protocol, instead, belongs to the class of on line probabilistic flooding. It has been shown through simulation that the three approaches can significantly decrease energy consumption and network load and increase the reliability of the broadcasting primi- tive over the GOSSIP protocol, resulting in promising solutions for energy constrained sensor networks.
It has also been shown that further performance improvement can be achieved for gossip by exploring network wide or local information [95]. For example, neighbor states are utilized to set the gossip probability in [95]. The simulation results show that a superior performance in terms of coverage, energy efficiency, per hop latency and overhead can be achieved. We take this approach a step further and investigate how various kinds of local neighborhood information can be explored to reduce the energy consumption for query dissemination in sensor networks.