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Broadcasting in wireless networks is vulnerable to adversarial jamming. Tothwart such behavior, \emph{resource competitive analysis} is proposed. In thisframework, sending, listening, or jamming on one channel for one time slotcosts one unit of energy. The adversary can employ arbitrary strategy todisrupt communication, but has a limited energy budget $T$. The honest nodes,on the other hand, aim to accomplish broadcast while spending only $o(T)$.Previous work has shown, in a $C$-channels network containing $n$ nodes, forlarge $T$ values, each node can receive the message in $\tilde{O}(T/C)$ time,while spending only $\tilde{O}(\sqrt{T/n})$ energy. However, thesemulti-channel algorithms only work for certain values of $n$ and $C$, and canonly tolerate an oblivious adversary.  In this work, we provide new upper and lower bounds for broadcasting inmulti-channel radio networks, from the perspective of resource competitiveness.Our algorithms work for arbitrary $n,C$ values, require minimal priorknowledge, and can tolerate a powerful adaptive adversary. More specifically,in our algorithms, for large $T$ values, each node's runtime is $O(T/C)$, andeach node's energy cost is $\tilde{O}(\sqrt{T/n})$. We also complementalgorithmic results with lower bounds, proving both the time complexity and theenergy complexity of our algorithms are optimal or near-optimal (within apoly-log factor). Our technical contributions lie in using "epidemic broadcast"to achieve time efficiency and resource competitiveness, and employing couplingtechniques in the analysis to handle the adaptivity of the adversary. At thelower bound side, we first derive a new energy complexity lower bound for1-to-1 communication in the multi-channel setting, and then apply simulationand reduction arguments to obtain the desired result.

Broadcasting Competitively against Adaptive Adversary in Multi-channel Radio Networks