The easiest way to provide high accessibility is to periodically broadcast (flood) service information to the entire network. This method entails major energy consumption, but it is simple and some protocols use this approach.To reduce the overhead associated with broadcasting, some protocols restrict the flooding area by forwarding packets in a specific direction, as cross shape or restricted regions. These schemes could reduce the broadcasting overhead but still require unnecessary replications if the service information is not popular. Load scalability is the ease with which a distributed system can expand and contract its resource pool to accommodate heavier or lighter loads; it is the ease with which a system or component can be modified, added, or removed to accommodate a changing load.
Service location protocols should rapidly provide service information with a large number of users. Therefore, load scalability is an important metric for a service location protocol [24�C40].In this paper, we propose an adaptive square-shaped trajectory (ASST)-based service location method, which is a novel self-configuring, scalable, energy efficient, and robust service location protocol. ASST is based on Geographic Hash Table (GHT) and Trajectory Based Forwarding (TBF). GHT maps the geographic position of a sensor network field to a hash table. In GHT, the sensor node closest to the position where is computed by hash function is responsible for a set of key and data [6,8,9,11].
ASST stores service information in groups of sensor nodes, called a trajectory.
A node wishing to publish (advertise) service information obtains a position through the hash function, and it then uses geographic-aided routing such as GPSR (Greedy Perimeter Stateless Routing) to store service information to the trajectory surrounding Entinostat the hashed position, as in GHT [6,7]. ASST uses TBF to form a trajectory storing the service information. Replication between nodes in the trajectory reduces the network load on a node because queries from users are distributed to several nodes in the trajectory. To further distribute the network load, ASST adjusts the range and size of the trajectory in proportion to the frequency of user queries.
In the next section, we review related work. Section 3 describes ASST, and Section 4 provides Drug_discovery performance evaluation. We conclude the paper in Section 5.2.?Related WorkConventional solutions related to this paper can be classified into the following two approaches: Data Storage architecture in a wireless sensor network and Service Location protocols in an ad hoc network, as shown in Table 1 [4,5,15,22,34,37,40].Table 1.Classification of Data Storage Schemes and Service Location Protocols.