Zigbee Tree Routing, which doesn‟t need any routing table/route discovery overhead is used in several resource limited devices and applications. ZTR has a basic limitation regarding providing of optimal routing path as it follows tree topology, hence an optimal routing path can‟t be achieved. In this paper, we proposed a protocol stated as Shortcut Tree Routing (STR) similar to ZTR‟s entities, such as low memory consumption, no route discovery overhead, providing nearest optimal routing path using hierarchical addressing scheme and calculating the remaining hops from source to destination. The specifications are unaltered, as STR uses just the addressing scheme and neighbor table in association with the Zigbee standards. The research process illustrates the 1Hop neighbor communication representation upgrades the overall network performance execution by splitting up of the traffic load concentrated on the tree links. The performance evaluation indicates, STR accomplishes the performances of AODV and ZTR in certain conditions of it, such as network density, configurations and network traffic patterns.

With reference to a distributed architecture consisting of sensor nodes connected in a wireless network, we present a model of a protection system based on segments and applications. An application is the result of the joint activities of a set of cooperating nodes. A given node can access a segment stored in the primary memory of a different node only by presenting a gate for that segment. A gate is a form of pointer protected cryptographically, which references a segment and specifies a set of access rights for this segment. Gates can be freely transmitted between nodes, thereby granting the corresponding access permissions. Two special node functionalities are considered, segment servers and application servers. Segment servers are used for inter-application communication and information gathering. An application server is used in each application to support key management and rekeying. The rekey mechanism takes advantage of key naming to cope with losses of rekey messages. The total memory requirements for key and gate storage result to be a negligible fraction of the overall memory resources of the generic network node.

With reference to a distributed architecture consisting of sensor nodes connected by wireless links in an arbitrary network topology, we consider a segment-oriented implementation of the single address space paradigm of memory reference. In our approach, applications consist of active entities called components, which are distributed in the network nodes. A component accesses a given segment by presenting a handle for this segment. A handle is a form of pointer protected cryptographically. Handles allow an effective implementation of communications between components, and key replacement. The number of messages generated by the execution of the communication primitives is independent of the network size. The key replacement mechanism is well suited to reliable application rekeying over an unreliable network.

Wireless sensor networks (WSNs) are typically deployed environments, often very hostile and without assistance. A certain level of security must be provided. However, the resource constraint is the most important characteristic of this network. Indeed, WSNs are limited in terms of calculation, CPU, battery, etc. Therefore, a solution that aims to conserve these resources is widely desired. In this paper, we focus on the problem of encryption algorithm complexity. Some of the existing encryption algorithms provide high calculation cost, require large memory and are not applicable for WSNs scenarios. Based on Feistel structure, we propose a novel ultra-lightweight encryption algorithm, named ULEA. Besides diffusion and confusion of data, ULEA assumes minor encryption rounds with simplified transformations and functions to complex the cipher. The security analysis and experimental results suggest that the ULEA algorithm is an appropriate, low storage space, energy-efficient encryption process with high security for WSNs.

Wireless sensor networks (WSNs) are nowadays considered as an important part of the Internet of Things (IoT). In these networks, data aggregation plays an essential role in energy preservation. However, WSNs are usually deployed in hostile and unattended environments (e.g. military applications) in which the confidentiality and integrity security services are widely desired. Recently, homomorphic encryptions have been applied to conceal sensitive information during aggregation such that algebraic operations are done directly on ciphertexts without decryption. The main benefit is that they offer the end-to-end data confidentiality and they do not require expensive computation at aggregator nodes since no encryption and decryption are performed. However, existing solutions either incur a considerable overhead or have limited applicability to certain types of aggregate queries. This paper presents a novel secure data aggregation protocol for WSNs. The scheme employs Stateful Public Key Encryption (StPKE) and some previous techniques in order to provide an efficient end-to-end security. Moreover, our solution does not impose any bound on the aggregation function's nature (Maximum, Minimum, Average, etc.). We present and implement our scheme on TelosB as well as MicaZ sensor network platforms and measure the execution time of our various cryptographic functions. Simulations are also conducted to show how our scheme can achieve a high security level (by providing the above security services) with a low overhead (in terms of computation and communication) in large-scale scenario.

Wireless sensor network is a self-organizing wireless network system which has enabled densely deployment of nodes. These wireless sensors gather and forward data. But finding an efficient route is a challenge while the nodes communicate for data transmission. A routing algorithm, FMCR, is proposed in this paper. A well-known operations research technique, multi-criteria decision analysis, is used in this proposed scheme. Here multiple criteria, such as residual energy, packet transmission frequency and hop count are taken into account. In order to assign the weighted values on each criterion, Fuzzy rules are applied on heuristic properties like node density, dead nodes and delay. The best route is selected using Weighted Product Model (WPM). This scheme has been implemented using TinyOS, an event-driven operating system designed for wireless sensor network.

Wireless sensor and actuator networks provide a distributed system composed of wirelessly connected smart sensor and actuator nodes, suitable for cost-efficient control applications. An important research challenge is deployment, where features like node auto-configuration, unattended operation, and Internet connectivity are becoming mandatory. Moreover, on off-the-shelf solutions the user typically must be network technology-savvy to take advantage of sensing and actuation services. This paper presents a novel multi-channel architecture for sensor data gathering and actuation, featuring Plug-and-Play like functionality for node attachment and operation, IPv6 at the node level, and dedicated communication semantic protocols-the ZenSens system architecture. The architecture features the sensor/actuator nodes, a personal computer application (SenseLab), a mobile application (SenseLab mobile), and World Wide Web access (WebSensor), presenting the user with a complete sensing and actuation solution. As a result the user can operate the network without technological background, and near-zero configuration. All developed software and firmware are presented, and validated through a series of experiments on real hardware, namely using a test-bed with TelosB motes running ContikiOS.

Wireless networked control systems use shared wireless links to communicate between sensors and controllers, and require a channel access policy to arbitrate access to the links. Existing multiple access protocols perform this role in an agnostic manner, by remaining insular to the applications that run over the network. This approach does not give satisfactory control performance guarantees. To enable the use of wireless networks in emerging industrial applications, we must be able to systematically design wireless networked control systems that provide guaranteed performances in resource-constrained networks.In this thesis, we advocate the use of state-based channel access policies. A state-based policy uses the state of the controlled plant to influence access to the network. The state contains information about not only the plant, but also the network, due to the feedback in the system. Thus, by using the state to decide when and how frequently to transmit, a control system can adapt its contribution to the network traffic, and enable the network to adapt access to the plant state. We show that such an approach can provide better performance than existing methods. We examine two different state-based approaches that are distributed and easy to implement on wireless devices: event-based scheduling and adaptive prioritization.Our first approach uses events to reduce the traffic in the network. We use a state-based scheduler in every plant sensor to generate non-coordinated channel access requests by selecting a few critical data packets, or events, for transmission. The network uses a contention resolution mechanism to deal with simultaneous channel access requests. We present three main contributions for this formulation. The first contribution is a structural analysis of stochastic event-based systems, where we identify a dual predictor architecture that results in separation in design of the state-based scheduler, observer and controller. The second contribution is a Markov model that describes the interactions in a network of event-based systems. The third contribution is an analysis of the stability of event-based systems, leading to a stabilizing design of event-based policies.Our second approach uses state-based priorities to determine access to the network. We use a dominance protocol to evaluate priorities in a contention-based setting, and characterize the resulting control performance. An implementation and evaluation of this channel access mechanism on sensor nodes is also presented.The thesis finally examines the general networked control problem of jointly optimizing measurement and control policies, when a nonlinear measurement policy is used to perform quantization, event-triggering or companding. This contribution focuses on some of the fundamental aspects of analyzing and synthesizing control systems with state-based measurement policies in a more generalized setting. We comment on the dual effect, certainty equivalence and separation properties for this problem. In particular, we show that it is optimal to apply separation and certainty equivalence to a design problem that permits a dynamic choice of the measurement and control policies.

Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged—known as the Internet-of-Things (IoT)—where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies— mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative—leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot—embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time—often devices are in failure for hours. Second, a device’s behavior effects the amount of energy they can harvest—meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and nonintuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly.

Wireless Sensor Networks are composed by resource constrained devices. Communication is a key issue concerning energy consumption, and thus it is important to optimize data routing. Despite the energy-aware routing protocols proposed, there is a gap concerning the use of energy as a routing metric in software-defined wireless sensor networks (SDWSN). This paper presents an SDWSN energy-aware routing approach. Results obtained using the TinySDN framework show that combining energy and ETX (Expected Transmission Count) metrics improve data delivery rates and increases the network lifetime. Keywords— Wireless Sensor Networks; software-defined networking; energy aware routing.

Wireless Sensor Networks (WSNs) are formed by hundreds of sensor nodes that are distributed autonomously within the sensing area.  It also incorporates with a gateway that provides wireless connection to communicate among nodes and pass data to one and another.  There are various applications using WSNs such as wildlife monitoring, environmental monitoring and smart space.  The limitation of WSNs is that they are only dependable on power battery to ensure their lifetime as a sensing device. Thus, in order to prolong the network lifetime, various research has been done including the development of energy efficient routing protocols.  One of the earliest techniques is Low Energy Adaptive Clustering Hierarchy (LEACH).  LEACH protocol uses randomization to select cluster head in order to have an evenly distributed energy among nodes.  This work provides an in depth knowledge of LEACH protocol and how it is implemented on TinyOS using a TelosB mote.  By implementing a conventional protocol which is Direct Transmission (DT) along with LEACH protocol in nodes, a significant impact on energy dissipation of protocols can be examined. In the findings, LEACH protocol energy usage in transmitting data can be evenly minimized thus lifetime of nodes can be longer.  The result shows LEACH saves up to 30% of energy saving than using DT protocol.

Wireless Sensor Network(WSN) consists of sensor nodes which are deployed densely in an area of interest. The area is intended to be sensed or monitored. Each sensor node is a tiny and power constrained device which is assigned the task of monitoring. One of the most important requirements for wireless sensor networks is systematic collection of data, where sensed data are collected at sensor nodes and forwarded to a base station through number of hops for further processing. This paper presents an event-driven data gathering scheme in a Sensor-Cloud infrastructure. The scheme uses Fuzzy logic to ensure efficient data collection and report a select set of data which is required. Aim of this work is to minimal use of communication resource and reduce overhead while collecting sensor data. Also, an attempt is made to implement the scheme on Tiny OS using TelosB motes for real-time testing.

Wireless Sensor Network (WSN) is one of the most demanding research topics prevalent in the modern research domain. WSN consists of densely deployed sensor nodes in the area which is to be sensed or monitored. Every tiny sensor node needs to transmit the sensed data to more powerful sink nodes. Sensed data may reach sink node through multiple hops. As the sensor nodes are resource constrained, most of the data forwarding algorithms employ threshold values of key parameters and implement event driven routes. Instead, we consider multiple parameters simultaneously for determining route to send the data to sink. In this paper, we propose routing scheme using Multi Criteria Decision Making technique where each criterion is assigned with a weight. An adaptive learning method is used to determine the weights. This routing scheme ensures robust packet reception ratio.

Wireless Integrated Network Sensors (WINS) now provide a new monitoring and control capability for monitoring the borders of the country. WINS combine sensing, signal processing, decision capability, and wireless networking capability in a compact, low power system. Using this concept we can easily identify a stranger or some terrorists entering the border. The border area is divided into number of nodes. Each node is in contact with each other and with the main node. The noise produced by the foot-steps of the stranger is collected using the sensor. This sensed signal is then converted into power spectral density and then compared with reference value of our convenience. Accordingly the compared value is processed using a microprocessor, which sends appropriate signals to the main node. Thus the stranger is identified at the main node. A series of interface, signal processing, and communication systems have been implemented in micro power CMOS circuits. A micro power spectrum analyzer has been developed to enable low power operation of the entire WINS system. But it is very cheaper when compared to other security systems such as RADAR under use. It produces a less amount of delay. Hence it is reasonably faster.

Wide deployment of wireless sensor and actuator networks in cyber-physical systems requires systematic design tools to enable dynamic tradeoff of network resources and control performance. In this paper, we consider three recently proposed aperiodic control algorithms which have the potential to address this problem. By showing how these controllers can be implemented over the IEEE 802.15.4 standard, a practical wireless control system architecture with guaranteed closed-loop performance is detailed. Event-based predictive and hybrid sensor and actuator communication schemes are compared with respect to their capabilities and implementation complexity. A two double-tank laboratory experimental setup, mimicking some typical industrial process control loops, is used to demonstrate the applicability of the proposed approach. Experimental results show how the sensor communication adapts to the changing demands of the control loops and the network resources, allowing for lower energy consumption and efficient bandwidth utilization.

While it is essential to exploit in-network processing in wireless sensor networks in order to save bandwidth and energy, we are constrained by the limited storage available in off-the-shelf sensor devices. NAND flash memory has great potential for extending storage capacity for sensor applications. Since each sensor platform is typically equipped with limited main memory and sensor data, as well as the fact that queries are temporal, existing flash index or file systems for general portable devices are not suitable for sensor networks. We propose Time-Log Tree (TL-Tree), a novel unbalanced and cascaded structure, that takes advantage of available flash capacity while making use of the time-series property as a primary feature for optimizing both memory and energy constraints. Extensive experiments show TL-Tree's ability to utilize both flash capacity and temporal locality to support sensor data processing. Compared to other schemes, it achieves much better access and energy savings for different kinds of random and temporal range queries. In addition, TL-Tree can also be easily extended to support value-based queries. We have developed a hardware board that includes a raw 128MB NAND flash chip on MicaZ mote. We have also implemented a flash driver and the TL-Tree to demonstrate the practicality of this idea.

We present a model of a protection system based on passwords, protection contexts and protection domains.A protection context is a set of access rights for the memory pages.Passwords are associated with protection domains, which are sets of protection contexts.At the hardware level, the model is supported by a memory protection unit interposed between the processor and the main memory. With reference to an embedded system featuring no support for memory management, we present a model of a protection system based on passwords. At the hardware level, our model takes advantage of a memory protection unit (MPU) interposed between the processor and the complex of the main memory and the input-output devices. The MPU supports both concepts of a protection context and a protection domain. A protection context is a set of access rights for the memory pages; a protection domain is a set of one or more protection contexts. Passwords are associated with protection domains. A process that holds a given password can take advantage of this password to activate the corresponding domain. A small set of protection primitives makes it possible to modify the composition of the domains in a strictly controlled fashion.The proposed protection model is evaluated from a number of important viewpoints, which include password distribution, review and revocation, the memory requirements for storage of the information concerning protection, and the time necessary for password validation. Display Omitted

We introduce a state-based distributed prioritization mechanism for a sensor associated with a dynamical system to access a wireless network, when multiple such systems share the same network link. The priorities, designated Attention Factors, are assigned by each sensor to its data packets, based on measurements of the system state. The Attention Factor represents a quantized value of the minimum risk in not transmitting a given measurement. The Attention Factors from different sensors are evaluated and allotted slots, in a distributed manner, using a dominance-based protocol called tournaments. Packets with the same Attention Factor in a tournament collide, and are lost. We analytically evaluate the probability of a successful transmission using this access mechanism. We also find an upper bound for the estimation and control performance of a system using tournament access, which shows the benefits of using state-based priorities. The proposed tournament mechanism is implemented on the IEEE 802.15.4 standard protocol stack, and evaluated in a hardware-in-the-loop experimental setup.

We believe that the existing 802.11 MAC layer can be optimized (especially for energy-efficiency) to make Wi-Fi suitable for a wide range of IoT applications. However, there is a lack of low-cost embedded platforms to be used for experimentation with 802.11 MAC. The majority of low-power Wi-Fi modules for embedded systems has closed source firmware and protocol stack implementations, which prevents implementation and testing of new protocol features. Here we describe Contiki80211, an open source 802.11 radio link layer implementation for Contiki OS, optimized for resource constrained embedded platforms, whose purpose is to enable experimentation with 802.11 MAC layer management mechanisms on embedded devices.

This thesis studies the potential of a novel approach to ensure more efficient and intelligent assignment of capacity through medium access control (MAC) in practical wireless sensor networks (WSNs), whereby Reinforcement Learning (RL) is employed as an intelligent transmission strategy. RL is applied to framed slotted-ALOHA to provide perfect scheduling. The system converges to a steady state of a unique transmission slot assigned per node in single-hop and multi-hop communication if there is sufficient number of slots available in the network, thereby achieving the optimum performance. The stability of the system against possible changes in the environment and changing channel conditions is studied. A Markov model is provided to represent the learning behaviour, which is also used to predict how the system loses its operation after convergence. Novel schemes are proposed to protect the lifetime of the system when the environment and channel conditions are insufficient to maintain the operation of the system. Taking real sensor platform architectures into consideration, the practicality of MAC protocols for WSNs must be considered based on hardware limitations/constraints. Therefore, the performance of the schemes developed is demonstrated through extensive simulations and evaluations in various test-beds. Practical evaluations show that RL-based schemes provide a high level of flexibility for hardware implementation.