Abstract
Multiple access channel (MAC) networks use a broadcasting algorithm called the Binary Exponential Backoff (BEB) to mediate access to the shared communication channel by competing nodes and resolve their collisions. While the BEB achieves fair throughput and average packet latency in jamming-free environments and relatively small networks, its performance noticeably degrades when the network is exposed to jamming or its size increases. This paper presents an alternative broadcasting algorithm called the K-tuple Full Withholding (KTFW), which significantly increases MAC networks’ resilience to jamming attacks and network growth. Through simulation, we compare the KTFW with both the BEB and the Queue Backoff (QB), an efficient and high-throughput broadcasting algorithm. We compare the three approaches against two different traffic injection models, each approximating a different environment type. Our results show that the KTFW achieves higher throughput and lower average packet latency against jamming attacks than both the BEB and the QB algorithms. The results also show that the KTFW outperforms the BEB for larger networks with or without jamming.
Highlights
Ethernet and wireless local area networks (WLANs) have become the main building blocks of TCP/IP networks
Our evaluation shows that the K-tuple Full Withholding (KTFW) algorithm makes multiple access channel (MAC) networks significantly more resilient to jamming attacks than the binary exponential backoff (BEB) and the Queue Backoff (QB) algorithms
We proposed a novel broadcast algorithm, called the KTFW algorithm, that is more resilient to jamming attacks and is scalable for larger networks
Summary
Ethernet and wireless local area networks (WLANs) have become the main building blocks of TCP/IP networks. We compare the KTFW with both the standard BEB and the queue backoff (QB) [19], a high-throughput broadcast algorithm, and measure their performances in terms of throughput and average packet latency under various traffic injection models, jamming rates, and network sizes. We quantify these performance metrics for two different adversarial models of packet injection: the leaky bucket injection model (LBIM) and the randomized injection model (RIM) [20,21].
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