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Security and quality of service (QoS) issues in cluster-based wireless sensor networks are investigated. The QoS perspective is mostly at application level consisting of four attributes, which are spatial resolution, coverage, system lifetime and packet loss due to collisions. The addressed security aspects are message integrity and authentication. Under this scope, the interactions between security and service quality are analyzed with particular emphasis on the tradeoff between security and spatial resolution for channel capacity. The optimal security and spatial resolution levels which yield the best tradeoff are determined. In addition, a control strategy is proposed to achieve the desired quality of service and security levels during the entire operation of a cluster-based sensor network. Compared to the existing studies, the proposed method is simpler and has superior performance.

Today, wireless sensor networks (WSNs) are no longer a nascent technology and future networks, especially Cyber-Physical Systems (CPS) will integrate more sensor-based systems into a variety of application scenarios. Typical application areas include medical, environmental, military, and commercial enterprises. Providing security to this diverse set of sensor-based applications is necessary for the healthy operations of the overall system because untrusted entities may target the proper functioning of applications and disturb the critical decision-making processes by injecting false information into the network. One way to address this issue is to employ en-route-filtering-based solutions utilizing keys generated by either static or dynamic key management schemes in the WSN literature. However, current schemes are complicated for resource-constrained sensors as they utilize many keys and more importantly as they transmit many keying messages in the network, which increases the energy consumption of WSNs that are already severely limited in the technical capabilities and resources (i.e., power, computational capacities, and memory) available to them. Nonetheless, further improvements without too much overhead are still possible by sharing a dynamically created cryptic credential. Building upon this idea, the purpose of this thesis is to introduce an efficient and secure communication framework for WSNs. Specifically, three protocols are suggested as contributions using virtual energies and local times onboard the sensors as dynamic cryptic credentials: (1) Virtual Energy-Based Encryption and Keying (VEBEK); (2) TIme-Based DynamiC Keying and En-Route Filtering (TICK); (3) Secure Source-Based Loose Time Synchronization (SOBAS) for WSNs.

Our work focuses on wireless networks in general, but deals specifically with security in wireless sensor networks and energy consumption in IEEE 802.11 infrastructure WLANs. In the first part of our work, we focus on secure communication among sensor nodes in a wireless sensor network. These networks consists of large numbers of devices having limited energy and memory. Public key cryptography is too demanding for these resource-constrained devices because it requires high computation. So, we focus on symmetric key cryptography to achieve secure communication among nodes. For this cryptographic technique to work, two nodes have to agree upon a common key. To achieve this, many key distribution schemes have been proposed in the literature. Recently, several researchers have proposed schemes in which they have used group-based deployment models and assumed predeployment knowledge of the expected locations of nodes. They have shown that these schemes achieve better performance than the earlier schemes, in terms of connectivity, resilience against node capture and storage requirements. But in many situations expected locations of nodes are not available. We propose a solution which does not use the group-based deployment model and predeployment knowledge of the locations of nodes, and yet performs better than schemes which make the aforementioned assumptions. In our scheme, groups are formed after the deployment of sensor nodes on the basis of their physical locations. Nodes in different groups sample keys from disjoint key pools, so that compromise of a node affects secure links of its group only. Because of this reason, our scheme performs better than earlier schemes as well as the schemes using predeployment knowledge, in terms of connectivity, storage requirement, and security. Moreover, the post-deployment key generation process completes sooner than in schemes like LEAP+. In the second part of our work, we develop analytical models for estimating the energy spent by stations (STAs) in infrastructure WLANs when performing TCP-controlled file downloads. We focus on the energy spent in radio communication when the STAs are in the Continuously Active Mode (CAM), or in the static Power Save Mode (PSM). Our approach is to develop accurate models for obtaining the fractions of times the STA radios spend in idling, receiving and transmitting. We discuss two traffic models for each mode of operation: (i) each STA performs one large file download, and (ii) the STAs perform short file transfers with think times (short duration of inactivity)between two transfers. We evaluate the rate of STA energy expenditure with long file downloads, and show that static PSM is worse than using just CAM. For short file downloads, we compute the number of file downloads that can be completed with a given battery capacity, and show that PSM performs better than CAM for this case. We provide a validation of our analytical models using the NS-2 simulator. Although the PSM performs better than the CAM when the STAs download short files over TCP with think times, its performance degrades as the number of STAs associated to the access point (AP) increases. To address this problem, we propose an algorithm, which we call opportunistic PSM (OPSM). We show through simulations that OPSM performs better than PSM. The performance gain achieved by OPSM increases as the file size requested by the STAs or the number of STAs associated with the AP increases. We implemented OPSM in NS-2.33, and to compare the performance of OPSM and PSM, we evaluate the number of file downloads that can be completed with a given battery capacity and the average time taken to download a file.