Delay compensation using Smith predictor for wireless network control system

Wireless Sensor Network (WSN) is widely used in the industrial Network Control System (NCS). It relies on the IEEE 802.15.4 MAC protocol to transfer data at low rate. Experimental and theoretical studies proved that the wireless channel produces a time delay. In the NCS, this delay may cause system instability and performance degradation. Delay compensation schemes are used to reduce the delay effects. In this paper, a delay compensation scheme using classical and adaptive Smith predictor is applied to wireless NCS. The Markov model is proposed to compute the estimated network delay used in the classical predictor. In the adaptive predictor, the channel delay statistics using shift register is proposed to update the estimated delay. To evaluate the proposed schemes, a DC-motor controller system based on IEEE 802.15.4 is built using True Time Matlab software. The system performance with and without the proposed delay compensation scheme is studied. It is also compared to other delay compensation schemes. The results show that the proposed scheme improves the NCS performance significantly and reduces the effect of the delay on the system

Moving-Target Defense in Depth: Pervasive Self- and Situation-Aware VM Mobilization across Federated Clouds in Presence of Active Attacks

Federated clouds are interconnected cooperative cloud infrastructures offering vast hosting capabilities, smooth workload migration and enhanced reliability. However, recent devastating attacks on such clouds have shown that such features come with serious security challenges. The oblivious heterogeneous construction, management, and policies employed in federated clouds open the door for attackers to induce conflicts to facilitate pervasive coordinated attacks. In this paper, we present a novel proactive defense that aims to increase attacker uncertainty and complicate target tracking, a critical step for successful coordinated attacks. The presented systemic approach acts as a VM management platform with an intrinsic multidimensional hierarchical attack representation model (HARM) guiding a dynamic, self and situation-aware VM live-migration for moving-target defense (MtD). The proposed system managed to achieve the proposed goals in a resource-, energy-, and cost-efficient manner