This paper investigates the problem of computing the optimal
trajectories of multiple data MULEs (e.g., robots, vehicles, etc.) to minimize
data collection latency in wireless sensor networks. By relying on a slightly
different assumption, we define two interesting problems, the k-traveling
salesperson problem with neighborhood ( k-TSPN) and the k-rooted path cover
problem with neighborhood (k-PCPN). Since both problems are NP-hard, we propose
constant factor approximation algorithms for them along with two simpler
heuristic algorithms. We also conduct simulations to compare the performance of
the proposed approaches with the existing alternatives. Our simulation results
indicate that the proposed algorithms outperform the competitors on average.
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