Efficient And Confident Protocols In Safety Critical Wireless Sensor Networks

Safety critical wireless sensor networks usually require critical guarantees of reliability, real time and safety protection of the wireless sensor networks, which ensures effective, timely, reliable and secure data transmission. The potential applications of the safety critical systems involve industrial monitoring and control, intelligent transportation system and intelligent medical treatment, which have broad and essential application prospects.The features of the safety critical wireless sensor networks, such as dynamicity and open environment pose great challenges for designing efficient and confident protocols for wireless sensor networks. When designing protocols, it is essential to take the non-deterministic factors into consideration, such as limited resources, random topology, to overcome the drawbacks such as the unbalanced energy distribution, short network lifetime and inadequacy of safety estimation for developing the effective, real time, safe and confident protocol infrastructure of the wireless sensor networks. In this paper, we focus on studying and solving the existing problems from the perspectives of transmission efficiency, network fault tolerance, network security and privacy. The research issues can be summarized as follows.(1) Efficient data aggregation protocol based on ant colony optimization. The efficiency of the data aggregation influences the distribution of the energy cost of the network, which has a great impact on the lifetime of the network. Existing methods lack of the designing and maintaining of the dynamical topology, which leads to great consumption of the energy cost and unbalanced energy cost. In this paper, we design a class of efficient data aggregation algorithms based on the ant colony optimization for the wireless sensor networks (Data Aggregation based on Ant Colony Algorithm, DAACA), which combine the theory of the ant colony optimization with the data aggregation protocol. The pheromones in ant colony optimization are used for determining the merging node and selecting the next hop. Then the dynamical energy-aware network topology is constructed for balancing the energy cost and reducing the transmission hops. We develop the way of adjusting pheromones for adjusting the network topology, which optimizes the data aggregation tree. Based on these, we propose three heuristic algorithms, which optimize the adjustments of the pheromones from the perspective of global, threshold and ant colony system for further promoting the transmission efficiency and save costs. Experimental results reveal that, DAACA has longer lifetime, lower average energy cost and fewer transmission hops. (2) Real time fault tolerant protocol based on jumping transmission. The real time fault tolerant routing protocol guarantees the faulty nodes will never cause the network interrupt, data loss or network congestion, which is the basis of the confident transmission of the networks. Existing real time fault tolerant protocols underestimate the influences of the potential congestion, lack of feedback mechanism and have low transmission success ratio. In this paper, we propose a real time fault tolerant routing protocol (Dynamic juMping Real time Fault tolerant protocol, DMRF) for safety critical wireless sensor networks. When the network works normally, data are transmitted hop-by-hop from the source node to the sink node. If network congestion, faulty nodes, void region exist, or the remaining time ratio of the data packet is approaching the threshold, packets will be transmitted in a jumping mode to avoid these three circumstances, which reduce the transmission latency and enhance the transmission successful rate. Experimental results manifest that DMRF can effectively avoid the influences of the faulty nodes, network congestion and void region, it is a low complexity, efficient and low cost real time fault tolerant routing protocol.(3) Network vulnerability evaluation and selfish nodes avoidance. The safety critical wireless sensor networks are prone to various attacks and the behaviors of the nodes are difficult to control. To migrate the destructiveness of the attack, a common method is to use the vulnerability evaluation to enhance the security level of the vulnerable points. However, the precision of the previous methods in the vulnerability of the network and destructiveness of the attack are low. In the perspective of the selfish behavior avoidance, although, existing methods can detect the selfish nodes, the mechanisms of controlling the selfish behavior are lacked. In this paper, we focus on vulnerability evaluation and selfish nodes avoidance for the safety critical wireless sensor networks. In the vulnerability evaluation aspect, we propose the evaluation methods for static network and dynamic network under the node compromise attack. We analyze the vulnerable point from an adversarial point and transform the vulnerability evaluation to the destructiveness evaluation of the attacker. In the static network, based on the key sharing relationships between nodes, links, paths and routes, we develop modeling for estimating the destructiveness in terms of attacking graphs, matrix and energy efficiency. For the dynamical network, we construct the connected dominating set as the virtual backbone. We analyze the destructiveness when attacking the nodes in the backbone in a centralized and distributed way respectively to seek for maximum destructiveness. In the perspective of selfish behavior limitation, game theory is applied in designing the communication process between nodes. We regulate the behaviors of the nodes within clusters and among clusters, which avoids the destruction to the networks. Simulation results show that, in the vulnerability evaluation aspect, our methods owns higher attacking efficiency and more destructiveness, which indicates more precise vulnerability evaluation. In selfish behavior avoidance aspect, our methods can effectively regulate the behaviors of the network, which limits the selfish nodes’ behaviors as same as the normal nodes. This characteristic balances the energy cost of the network and prolongs the lifetime.(4) Network privacy protection algorithms based on combined clustering. In the safety critical wireless sensor networks, the location information and identity information are recorded in the data packets. Once the packets are intercepted, the location information and data information of the nodes will be destroyed. Although existing approaches use the spatial and temporal methods to conceal the exact location information of the nodes, they neglect to analyze the inner relationships between location and information. Therefore, to protect the location information, we need to take actions from both location information and data information. In our works, we develop a combined clustering algorithm (Enhanced ClusterCloak, ECC) for protecting location privacy and data privacy simultaneously. In location privacy protecting aspect, K-means clustering is used for diving regions iteratively, which meets the needs of K-anonymity while guaranteeing the region privacy. In the data privacy protection aspect, the hierarchical clustering is applied, which forbids the attacker from figuring out the real identities of the nodes. Simulation results indicate that ECC can provide nodes with higher anonymity level than expected, and it can protect the location privacy for the nodes while providing more exact data information.