An Energy-conscious Transport Protocol for Multi-hop Wireless Networks

We present a transport protocol whose goal is to reduce power consumption without compromising delivery requirements of applications. To meet its goal of energy efficiency, our transport protocol (1) contains mechanisms to balance end-to-end vs. local retransmissions; (2) minimizes acknowledgment traffic using receiver regulated rate-based flow control combined with selected acknowledgements and in-network caching of packets; and (3) aggressively seeks to avoid any congestion-based packet loss. Within a recently developed ultra low-power multi-hop wireless network system, extensive simulations and experimental results demonstrate that our transport protocol meets its goal of preserving the energy efficiency of the underlying network.Defense Advanced Research Projects Agency (NBCHC050053

Droplet: A New Denial-of-Service Attack on Low Power Wireless Sensor Networks

In this paper we present a new kind of Denial-of-Service attack against the PHY layer of low power wireless sensor networks. Overcoming the very limited range of jamming-based attacks, this attack can penetrate deep into a target network with high power efficiency. We term this the Droplet attack, as it attains enormous disruption by dropping small, payload-less frame headers to its victim's radio receiver, depriving the latter of bandwidth and sleep time. We demonstrate the Droplet attack's high damage rate to full duty-cycle receivers, and further show that a high frequency version of Droplet can even force nodes running on very low duty-cycle MAC protocols to drop most of their packets

Performance and Energy-Tuning Methodology for Wireless Sensor Networks Using TunableMAC

Energy-efficiency and performance are at the forefront with regards to wireless sensor networks due to the resource-constrained nature of the sensors on the network. Most of the energy in a sensor is consumed by the radio and this therefore creates the need for a more efficient use of the Media Access Control (MAC) layer which controls access to the radio. The Castalia framework which runs on the OMNET++ simulation platform provides a MAC layer protocol – TunableMAC – which is used in this paper for tuning of performance and consumed power. Our goal is to improve as much as possible the performance/energy balance in terms of resources used up by security features, while attempting to preserve the overall lifespan of the wireless sensors. This paper investigates performance parameters for TunableMAC such as energy consumed, latency, throughput and network lifetime based on simulated temperature sensors. A 5-step methodology is proposed that can be helpful for minimizing the impact of denial-of-sleep (DOS) attacks. Hence, the benefit of this research is that it feeds into the development of a novel MAC protocol that is energy-aware and can autonomously guard against energy drain attacks such as DOS attacks

Performance Analysis of Denial-of-Sleep Attack-Prone MAC Protocols in Wireless Sensor Networks

Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. On the other hand, the presence as well as the absence of security features implemented in resource constrained sensors can have negative effects on their energy consumption. Indeed, the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection could give room for energy-drain attacks such as denial-of-sleep attacks which has a higher negative impact on the life span (availability) of the sensors than the presence of security techniques. This paper focuses on denial-of-sleep attacks by simulating three Media Access Control (MAC) protocols – Sensor-MAC, Timeout-MAC and TunableMAC – under different network sizes. We evaluate, compare, and analyse the received signal strength and the link quality indicators for each of these protocols. The results of our simulation provide insight into how these parameters can be used to detect a denial-of-sleep attack. Finally, we propose a novel architecture for tackling denial-of-sleep attacks by propagating relevant knowledge via intelligent agents