Congestion Avoidance Energy Efficient MAC Protocol for Wireless Sensor Networks

Wireless Sensor Network (WSNs) are generally energy-constrained and resource-constrained. When multiple simultaneous events occur in densely deployed WSNs, nodes near the base station can become congested, decreasing the network performance. Additionally, multiple nodes may sense an event leading to spatially-correlated contention, further increasing congestion. In order to mitigate the effects of congestion near the base station, an energy-efficient Media Access Control (MAC) protocol that can handle multiple simultaneous events and spatially-correlated contention is needed. Energy efficiency is important and can be achieved using duty cycles but they could degrade the network performance in terms of latency. Existing protocols either provide support for congestion near the base station or for managing spatially-correlated contention. To provide energy-efficiency while maintaining the networks performance under higher traffic load, we propose an energy-efficient congestion-aware MAC protocol. This protocol provides support for congestion near the base station and spatially-correlated contention by employing a traffic shaping approach to manage the arrival times of packets to the layers close to the base station. We implemented our protocol using the ns-2 simulator for evaluating its performance. Results show that our protocol has an improvement in the number of packets received at the base station while consuming less energy

Secure network programming in wireless sensor networks

Network programming is one of the most important applications in Wireless Sensor Networks as It provides an efficient way to update program Images running on sensor nodes without physical access to them. Securing these updates, however, remains a challenging and important issue, given the open deployment environment of sensor nodes. Though several security schemes have been proposed to impose the authenticity and Integrity protection on network programming applications, they are either energy Inefficient as they tend to use digital signature or lacks the data confidentiality. In addition, due to the absence of secure memory management in the current sensor hardware, the attacker could inject malicious code into the program flash by exploiting buffer overflow In the memory despite the secure code dissemination. The contribution of this thesis Is to provide two software-based security protocols and one hardware-based remote attestation protocol for network programming application. Our first protocol deploys multiple one-way key chains for a multi-hop sensor network. The scheme Is shown to be lower In computational, power consumption and communication costs yet still able to secure multi•hop propagation of program images. Our second protocol utilizes an Iterative hash structure to the data packets in network programming application, ensuring the data confidentiality and authenticity. In addition, we Integrated confidentiality and DoS-attack-resistance in a multi•hop code dissemination protocol. Our final solution is a hardware-based remote attestation protocol for verification of running codes on sensor nodes. An additional piece of tamper-proof hardware, Trusted Platform Module (TPM), is imposed into the sensor nodes. It secures the sensitive information (e.g., the session key) from attackers and monitors any platform environment changes with the Internal registers. With these features of TPM, the code Injection attack could be detected and removed when the contaminated nodes are challenged in our remote attestation protocol. We implement the first two software-based protocols with Deluge as the reference network programming protocol in TinyOS, evaluate them with the extensive simulation using TOSSIM and validate the simulation results with experiments using Tmote. We implement the remote attestation protocol on Fleck, a sensor platform developed by CSIRO that Integrates an Atmel TPM chip

Energy efficient scheduling for cluster-tree wireless sensor networks with time-bounded data flows: application to IEEE 802.15.4/ZigBee

Cluster scheduling and collision avoidance are crucial issues in large-scale cluster-tree Wireless Sensor Networks (WSNs). The paper presents a methodology that provides a Time Division Cluster Scheduling (TDCS) mechanism based on the cyclic extension of RCPS/TC (Resource Constrained Project Scheduling with Temporal Constraints) problem for a cluster-tree WSN, assuming bounded communication errors. The objective is to meet all end-to-end deadlines of a predefined set of time-bounded data flows while minimizing the energy consumption of the nodes by setting the TDCS period as long as possible. Sinceeach cluster is active only once during the period, the end-to-end delay of a given flow may span over several periods when there are the flows with opposite direction. The scheduling tool enables system designers to efficiently configure all required parameters of the IEEE 802.15.4/ZigBee beaconenabled cluster-tree WSNs in the network design time. The performance evaluation of thescheduling tool shows that the problems with dozens of nodes can be solved while using optimal solvers

Low-Power Embedded Design Solutions and Low-Latency On-Chip Interconnect Architecture for System-On-Chip Design

This dissertation presents three design solutions to support several key system-on-chip (SoC) issues to achieve low-power and high performance. These are: 1) joint source and channel decoding (JSCD) schemes for low-power SoCs used in portable multimedia systems, 2) efficient on-chip interconnect architecture for massive multimedia data streaming on multiprocessor SoCs (MPSoCs), and 3) data processing architecture for low-power SoCs in distributed sensor network (DSS) systems and its implementation. The first part includes a low-power embedded low density parity check code (LDPC) - H.264 joint decoding architecture to lower the baseband energy consumption of a channel decoder using joint source decoding and dynamic voltage and frequency scaling (DVFS). A low-power multiple-input multiple-output (MIMO) and H.264 video joint detector/decoder design that minimizes energy for portable, wireless embedded systems is also designed. In the second part, a link-level quality of service (QoS) scheme using unequal error protection (UEP) for low-power network-on-chip (NoC) and low latency on-chip network designs for MPSoCs is proposed. This part contains WaveSync, a low-latency focused network-on-chip architecture for globally-asynchronous locally-synchronous (GALS) designs and a simultaneous dual-path routing (SDPR) scheme utilizing path diversity present in typical mesh topology network-on-chips. SDPR is akin to having a higher link width but without the significant hardware overhead associated with simple bus width scaling. The last part shows data processing unit designs for embedded SoCs. We propose a data processing and control logic design for a new radiation detection sensor system generating data at or above Peta-bits-per-second level. Implementation results show that the intended clock rate is achieved within the power target of less than 200mW. We also present a digital signal processing (DSP) accelerator supporting configurable MAC, FFT, FIR, and 3-D cross product operations for embedded SoCs. It consumes 12.35mW along with 0.167mm2 area at 333MHz

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected

Communication platform for inter-satellite links in distributed satellite systems

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