Throughput maximization in multi-hop wireless networks under a secrecy constraint

• Published in: Computer networks (Amsterdam, Netherlands : 1999) Vol. 109; pp. 13 - 20
• Main Authors: Nardelli, Pedro H.J., Alves, Hirley, de Lima, Carlos H.M., Latva-aho, Matti
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 09.11.2016; Elsevier Sequoia S.A
• Subjects: Coding; Control units (computers); Design specifications; Hops; Industrial applications; Jamming; Links; Machine-to-machine communications; Messages; Multi-hop wireless networks; Nodes; Optimization; Relay; Security and jamming; Sensors; Stochastic geometry; Stochastic models; Studies; Throughput; Wireless networks; Stochastic geometry; Machine-to-machine communications; Throughput; Security and jamming; Multi-hop wireless networks
• ISSN: 1389-1286; 1872-7069
• DOI: 10.1016/j.comnet.2016.06.020

This paper analyzes the achievable throughput of multi-hop sensor networks for industrial applications under a secrecy constraint and malicious jamming. The evaluation scenario comprises sensors that measure some relevant information of the plant that is first processed by an aggregator node and then sent to the control unit. To reach the control unit, a message may travel through relay nodes, which form a multi-hop wireless link. At every hop, eavesdropper nodes attempt to acquire the messages transmitted through the legitimate link. The communication design problem posed here is how to maximize the multi-hop throughput from the aggregator to the control unit by finding the best combination of relay positions (i.e. hop length: short or long) and coding rates (i.e. high or low spectral efficiency) so that the secrecy constraint is satisfied. Using a stochastic-geometry formulation, we show that the optimal choice of coding rate is normally high and depends on the path-loss exponent only, while a greater number of shorter hops are preferable to smaller number of longer hops in any situation. For the investigated scenarios, we prove that the optimal throughput subject to the secrecy constraint achieves the unconstrained optimal performance – if a feasible solution exists.