Optimizing Transmission and Shutdown for Energy-Efficient Packet Scheduling in Sensor Networks

Energy-efficiency is imperative to enable the deployment of sensor networks with satisfactory lifetime. Conventional power management in radio communication primarily focuses independently on the physical layer, medium access control (MAC) or routing and approaches differ depending on the levels of abstraction. At the physical layer, the fundamental trade-off that exists between transmission rate and energy is exploited. This leads to the lazy scheduling approach, which consists of transmitting with the lowest power over the longest feasible duration. At MAC level, power reduction techniques tend to keep the transmission as short as possible to maximize the radio\u27s power-off interval. Those two approaches seem conflicting and it is not clear which one is the most appropriate for a given network scenario. In this paper, we propose a transmission strategy that combines both techniques optimally. We present a cross-layer solution to determine the best transmission strategy taking into account the transceiver power consumption characteristics, the system load and the scenario constraints. Based on this approach, we derive a low complexity, on-line scheduling algorithm that can be used to optimally organize the forwarding of the sensed information from cluster heads to the data sink (uplink) in a hierarchical sensor network. Results, considering Coded Frequency Shift Keying (FSK) modulation, show that depending on the scenario, a 50% extra power reduction is achieved in a realistic uplink data gathering context, compared to the case where only transmission rate scaling or shutdown is considered

Optimizing Transmission and Shutdown for Energy-Efficient Real-Time Packet Scheduling in Clustered Ad Hoc Networks

Energy efficiency is imperative to enable the deployment of ad hoc networks. Conventional power management focuses independently on the physical orMAC layer and approaches differ depending on the abstraction level. At the physical layer, the fundamental tradeoff between transmission rate and energy is exploited, which leads to transmit as slow as possible. At MAC level, power reduction techniques aim to transmit as fast as possible to maximize the radios power-off interval. The two approaches seem conflicting and it is not obvious which one is the most appropriate.We propose a transmission strategy that optimally mixes both techniques in a multiuser context.We present a cross-layer solution considering the transceiver power characteristics, the varying system load, and the dynamic channel constraints. Based on this, we derive a low-complexity online scheduling algorithm. Results considering an M-ary quadrature amplitude modulation radio show that for a range of scenarios a large power reduction is achieved, compared to the case where only scaling or shutdown is considered

Game Theoretical Approach for Joint Relay Selection and Resource Allocation in Mobile Device Networks

With the improvement of hardware, more and more multimedia applications are allowed to run in the mobile device. However, due to the limited radio bandwidth, wireless network performance becomes a critical issue. Common mobile solutions are based on the centralized structure, which require an access point to handle all the communication requirement in the work area. The transmission performance of centralized framework relies on the density of access points. But increasing the number of access points will cost lot of money and the interference between access point will reduce the transmission quality. Thanks to the wireless sensor network implementations, the distributed wireless network solution has been well studied. Now, many mobile network studies introduce the device to device idea which is a distributed structure of mobile network. Unlike wireless sensor networks, mobile networks have more movability and higher transmission speed requirement. In order to be used in mobile networks, a distributed network management algorithm needs to perform faster and more accurate. In this thesis, a new pairing algorithm is proposed to provide a better transmission quality for multimedia data. In the proposed approach, the multimedia data is quantized by distortion reduction. Then, the source-relay pairing solution is optimized by a history tracing system using game theory to improve the expected overall distortion reduction of the entire network. Several parameters are introduced in the proposed solution, so the optimization would fit for different situations. Simulation results show that the proposed algorithm achieves higher overall distortion reduction by avoiding the competition between nodes. Simulation results also show the parameters would affect the system performance, such as optimization speed, system stability and system overall transmit speed

Dynamic Power Management in Wireless Sensor Network

This research focuses on reducing or minimizing the power consumption, thereby increasing the network lifetime and also demonstrates a methodology for power consumption evaluation of WSN. The research also analyzes the energy consumption of ad hoc nodes using IEEE 802.11 interfaces; this was achieved using OPNET simulator. The evaluation takes into account the properties of the medium access protocol and the process of forwarding packets in ad hoc mode. The key point is to determine the node lifetime based on its average power consumption. The average power consumption is estimated considering how long the node remains sleeping, idle, receiving or transmitting

Energy Measurement and Profiling of Internet of Things Devices

As technological improvements in hardware and software have grown in leaps and bounds, the presence of IoT devices has been increasing at a fast rate. Profiling and minimizing energy consumption on these devices remains to be an an essential step towards employing them in various application domains. Due to the large size and high cost of commercial energy measurement platforms, the research community has proposed alternative solutions that aim to be simple, accurate, and user friendly. However, these solutions are either costly, have a limited measurement range, or low accuracy. In addition, minimizing energy consumption in IoT devices is paramount to their wide deployment in various IoT scenarios. Energy saving methods such as duty-cycling aim to address this constraint by limiting the amount of time the device is powered on. This process needs to be optimized, as devices are now able to perform complex, but energy intensive tasks due to advancements in hardware. The contributions of this paper are two-fold. First we develop an energy measurement platform for IoT devices. This platform should be accurate, low-cost, easy to build, and configurable in order to scale to the high volume and varying requirements for IoT devices. The second contribution is improving the energy consumption on a Linux-based IoT device in a duty-cycled scenario. It is important to profile and optimize boot up time and shutdown time, and improve the way user applications are executed. EMPIOT is an accurate, low-cost, easy to build, and flexible power measurement platform. We present the hardware and software components that comprise EMPIOT and then study the effect of various design parameters on accuracy. In particular, we analyze the effect of driver, bus speed, input voltage, and buffering mechanisms on sampling rate, measurement accuracy, and processing demand. In addition to this, we also propose a novel calibration technique and report the calibration parameters under different settings. In order to demonstrate EMPIOT\u27s scalability, we evaluate its performance against a ground truth on five different devices. Our results show that for very low-power devices that utilize 802.15.4 wireless standard, measurement error is less than 4%. In addition, we obtain less than 3% error for 802.11-based devices that generate short and high power spikes. The second contribution is the optimization the energy consumption of IoT devices in a duty cycled scenario by reducing boot up duration, shutdown duration, and user application duration. To this end, we study and improve the amount of time a Linux-based IoT device is powered on to accomplish its tasks. We analyze the processes of system boot up and shutdown on two platforms, the Raspberry Pi 3 and Raspberry Pi Zero Wireless, and enhance duty-cycling performance by identifying and disabling time consuming or unnecessary units initialized in the userspace. We also study whether SD card speed and SD card capacity utilization affect boot up duration and energy consumption. In addition, we propose Pallex, a novel parallel execution framework built on top of the systemd init system to run a user application concurrently with userspace initialization. We validate the performance impact of Pallex when applied to various IoT application scenarios: (i) capturing an image, (ii) capturing and encrypting an image, (iii) capturing and classifying an image using the the k-nearest neighbor algorithm, and (iv) capturing images and sending them to a cloud server. Our results show that system lifetime is increased by 18.3%, 16.8%, 13.9% and 30.2%, for these application scenarios, respectively

Converged IP-over-standard ethernet progress control networks for hydrocarbon process automation applications controllers

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The maturity level of Internet Protocol (IP) and the emergence of standard Ethernet interfaces of Hydrocarbon Process Automation Application (HPAA) present a real opportunity to combine independent industrial applications onto an integrated IP based network platform. Quality of Service (QoS) for IP over Ethernet has the strength to regulate traffic mix and support timely delivery. The combinations of these technologies lend themselves to provide a platform to support HPAA applications across Local Area Network (LAN) and Wide Area Network (WAN) networks. HPAA systems are composed of sensors, actuators, and logic solvers networked together to form independent control system network platforms. They support hydrocarbon plants operating under critical conditions that — if not controlled — could become dangerous to people, assets and the environment. This demands high speed networking which is triggered by the need to capture data with higher frequency rate at a finer granularity. Nevertheless, existing HPAA network infrastructure is based on unique autonomous systems, which has resulted in multiple, parallel and separate networks with limited interconnectivity supporting different functions. This created increased complexity in integrating various applications and resulted higher costs in the technology life cycle total ownership. To date, the concept of consolidating HPAA into a converged IP network over standard Ethernet has not yet been explored. This research aims to explore and develop the HPAA Process Control Systems (PCS) in a Converged Internet Protocol (CIP) using experimental and simulated networks case studies. Results from experimental and simulation work showed encouraging outcomes and provided a good argument for supporting the co-existence of HPAA and non-HPAA applications taking into consideration timeliness and reliability requirements. This was achieved by invoking priority based scheduling with the highest priority being awarded to PCS among other supported services such as voice, multimedia streams and other applications. HPAA can benefit from utilizing CIP over Ethernet by reducing the number of interdependent HPAA PCS networks to a single uniform and standard network. In addition, this integrated infrastructure offers a platform for additional support services such as multimedia streaming, voice, and data. This network‐based model manifests itself to be integrated with remote control system platform capabilities at the end user's desktop independent of space and time resulting in the concept of plant virtualization

A Solar-Powered Fertigation System based on Low-Cost Wireless Sensor Network Remotely Controlled by Farmer for Irrigation Cycles and Crops Growth Optimization

Nowadays, the technological innovations affect all human activities; also the agriculture field heavily benefits of technologies as informatics, electronic, telecommunication, allowing huge improvements of productivity and resources exploitation. This manuscript presents an innovative low cost fertigation system for assisting the cultures by using data-processing electronic boards and wireless sensors network (WSN) connected to a remote software platform. The proposed system receives information related to air and soil parameters, by a custom solar-powered WSN. A control unit elaborates the acquired data by using dynamic agronomic models implemented on a cloud platform, for optimizing the amount and typology of fertilizers as well as the irrigations frequency, as function also of weather forecasts got by on-line weather service