On Optimal Route of a Calibrating Mobile Sink in a Wireless Sensor Network

Energy-efficient topology control algorithm for maximizing network lifetime in wireless sensor networks with mobile sink

“…The mobile sink may visit each sensor node and gather its data (single-hop communication) [8][9][10][11][12][13][14][15] or may visit only a small portion of sensor nodes and gather data by multi-hop communication [16][17][18]3,[19][20][21]. In single-hop communication solution, since each node need not relay data for other nodes, energy consumption is minimized.…”

“…The maximum elements in L (3,10) , L (4,7) , and L (9,11) are l (3,10) (v 3 ) = 9 × 3 = 27, l (4,7) (v 1 ) = 4 × 6 = 24, and l (9,11) (v 2 ) = 6 × 4 = 24, respectively, so L (3,10) > L (4,7) and L (3,10) > L (9,11) . In addition, the second maximum elements in L (4,7) and L (9,11) are l (4,7) (v 2 ) = l(v 2 ) = 18 and l(v 1 ) (9,11) = l(v 1 ) = 20 respectively, so L (4,7) < L (9,11) . Thus, v 7 is chosen to add to U and connect with v 4 at this iteration.…”

Network Lifetime Maximization in Wireless Sensor Networks with a Path-Constrained Mobile Sink

“…One of the common approaches is to visit all the sensor nodes to receive data directly. The movement of the mobile sink follows the traveling salesman algorithm [12]. However, since the number of sensor nodes increases, the problem becomes intractable.…”

“…Since each member only needs the knowledge of the dual variable from the subsink node ( , ), the value of * , can be calculated locally. Now, we turn to the Lagrange dual problem corresponding to (12). The dual problem is to maximize the ( , ) with respect to ( , ): …”

Relay Hop Constrained Rendezvous Algorithm for Mobile Data Gathering in Wireless Sensor Networks

“…It is not difficult to conclude that direct-contact data collection is generally equivalent to the NP-complete TSP. Nesamony et al [8] formulated the traveling problem as TSP with Neighborhood, where a MC needs to visit the neighborhood of each sensor exactly once. He et al in [9] proposed a progressive optimization approach, called CSS, to reduce the tour length, and thus the data collection latency.…”