We present the design of a communication system that enables two devices to communicate using ambient RF as the only source of power. Our approach leverages existing TV and cellular transmissions to eliminate the need for wires and batteries, thus enabling ubiquitous communication where devices can communicate among themselves at unprecedented scales and in locations that were previously inaccessible.To achieve this, we introduce ambient backscatter, a new communication primitive where devices communicate by backscattering ambient RF signals. Our design avoids the expensive process of generating radio waves; backscatter communication is orders of magnitude more power-efficient than traditional radio communication. Further, since it leverages the ambient RF signals that are already around us, it does not require a dedicated power infrastructure as in traditional backscatter communication. To show the feasibility of our design, we prototype ambient backscatter devices in hardware and achieve information rates of 1 kbps over distances of 2.5 feet and 1.5 feet, while operating outdoors and indoors respectively. We use our hardware prototype to implement proof-of-concepts for two previously infeasible ubiquitous communication applications.

/pdf/ambient-backscatter-wireless-communication-out-of-thin-air-tm53bz3e4m.pdf

Ambient backscatter: wireless communication out of thin air

Recent advances in micro-electromechanical (MEMS) technology have led to the development of small, low-cost, and low-power sensors Wireless sensor networks (WSNs) are large-scale networks of such sensors, dedicated to observing and monitoring various aspects of the physical world In such networks, data from each sensor is agglomerated using data fusion to form a single meaningful result, which makes time synchronization between sensors highly desirable This paper surveys and evaluates existing clock synchronization protocols based on a palette of factors like precision, accuracy, cost, and complexity The design considerations presented here can help developers either in choosing an existing synchronization protocol or in defining a new protocol that is best suited to the specific needs of a sensor-network application Finally, the survey provides a valuable framework by which designers can compare new and existing synchronization protocols

/pdf/clock-synchronization-for-wireless-sensor-networks-a-survey-4xigbgjj02.pdf

Clock synchronization for wireless sensor networks: a survey

Wireless sensor networks (WSNs) use small nodes with constrained capabilities to sense, collect, and disseminate information in many types of applications. As sensor networks become wide-spread, security issues become a central concern, especially in mission-critical tasks. In this paper, we identify the threats and vulnerabilities to WSNs and summarize the defense methods based on the networking protocol layer analysis first. Then we give a holistic overview of security issues. These issues are divided into seven categories: cryptography, key management, attack detections and preventions, secure routing, secure location security, secure data fusion, and other security issues. Along the way we analyze the advantages and disadvantages of current secure schemes in each category. In addition, we also summarize the techniques and methods used in these categories, and point out the open research issues and directions in each area.

/pdf/sensor-network-security-a-survey-2ko4ukoih7.pdf

Sensor network security: a survey

Wireless sensor networks (WSNs) enable new applications and require non-conventional paradigms for protocol design due to several constraints. Owing to the requirement for low device complexity together with low energy consumption (i.e., long network lifetime), a proper balance between communication and signal/data processing capabilities must be found. This motivates a huge effort in research activities, standardization process, and industrial investments on this field since the last decade. This survey paper aims at reporting an overview of WSNs technologies, main applications and standards, features in WSNs design, and evolutions. In particular, some peculiar applications, such as those based on environmental monitoring, are discussed and design strategies highlighted; a case study based on a real implementation is also reported. Trends and possible evolutions are traced. Emphasis is given to the IEEE 802.15.4 technology, which enables many applications of WSNs. Some example of performance characteristics of 802.15.4-based networks are shown and discussed as a function of the size of the WSN and the data type to be exchanged among nodes.

https://www.mdpi.com/1424-8220/9/9/6869/pdf

An Overview on Wireless Sensor Networks Technology and Evolution

http://romisatriawahono.net/lecture/rm/survey/machine%20learning/Afsar%20-%20Clustering%20in%20Sensor%20Networks%20-%202014.pdf

Clustering in sensor networks

Advances in hardware and wireless network technologies have created low-cost, low-power, multifunctional miniature sensor devices. These devices make up hundreds or thousands of ad hoc tiny sensor nodes spread across a geographical area. These sensor nodes collaborate among themselves to establish a sensing network. A sensor network can provide access to information anytime, anywhere by collecting, processing, analyzing and disseminating data. Thus, the network actively participates in creating a smart environment.

/pdf/sensor-networks-an-overview-3wv28zusyd.pdf

Sensor networks: an overview

In this paper, we propose a novel decentralized traffic light control using wireless sensor network. The system architecture is classified into three layers; the wireless sensor network, the localized traffic flow model policy, and the higher level coordination of the traffic lights agents. The wireless sensors are deployed on the lanes going in and out the intersection. These sensors detect vehicles' number, speed, etc. and send their data to the nearest Intersection Control Agent (ICA) which, determines the flow model of the inter- section depending on sensors' data (e.g., number of vehicles approaching a specific intersection). Coping with dynamic changes in the traffic volume is one of the biggest challenges in intelligent transportation system (ITS). Our main contribution is the real-time adaptive control of the traffic lights. Our aim is to maximize the flow of vehicles and reduce the waiting time while maintaining fairness among the other traffic lights. Each traffic light controlled intersection has an intersection control agent that collects information from the sensor nodes. An intersection control agent manages its intersection by controlling its traffic lights. Multiple intersection agents can exchange information among themselves to control a wider area.

Adaptive Traffic Light Control with Wireless Sensor Networks

In a distributed sensor network, large number of sensors deployed which communicate among themselves to self-organize a wireless ad hoc network. We propose an energy-efficient level-based hierarchical system. We compromise between the energy consumption and shortest path route by utilizing number of neighbors (NBR) of a sensor and its level in the hierarchical clustering. In addition, we design a Secure Routing Protocol for Sensor Networks (SRPSN) to safeguard the data packet passing on the sensor networks under different types of attacks. We build the secure route from the source node to sink node. The sink node is guaranteed to receive correct information using our SRPSN. We also propose a group key management scheme, which contains group communication policies, group membership requirements and an algorithm for generating a distributed group key for secure communication.

A secure hierarchical model for sensor network

Real-time traffic light controllers (TLCs) play a major role in optimizing traffic flow. We uses wireless sensor network (WSN) to decrease vehicles' average trip waiting time (ATWT) on the road. We studied the performance of using one sensor and two sensors and designed corresponding controllers. In the case of one sensor we developed two models; a non-occupancy detection (NOD) and an occupancy detection (OD). NOD detects passing vehicles only whereas, OD detects vehicles that pass the sensor or stop at it. In both methods, we changed the sensor location relative to the traffic light's location. We then used two sensors to calculate number of vehicles waiting or approaching a traffic light. We tested different distances between these two sensors. Two sensors-based controller outperform the one sensor controller and produced results comparable to the ideal control that knows exact number of waiting vehicles. In analyzing our simulation, we found that the distance between the two sensors does not affect the performance of our design. Hence, placing both the sensors close to each others produce the best performance in terms of quality of the data and reduce energy consumption which leads to extending the life time of the WSN.

Wireless Sensor-Based Traffic Light Control

In this paper, we present a version of the linear hash structure algorithm to increase concurrency using multi-level transaction model. We exploit the semantics of the linear hash operations at each level of transaction nesting to allow more concurrency. We implement each linear hash operation by a sequence of operations at lower level of abstraction. Each linear hash operation at leaf-level is a combination of search and read/write operations. We consider locks at both vertex (page) and key level (tuple) to further increase concurrency. As undo-based recovery is not possible with multi-level transactions, we use compensation-based undo to achieve atomicity. We have implemented our model using object-oriented technology and multithreading paradigm. In our implementation, linear hash operations such as find, insert, delete, split, and merge are implemented as methods and correspond to multi-level transactions.

Malik Ayed Tubaishat

Papers

Sensor networks: an overview

Adaptive Traffic Light Control with Wireless Sensor Networks

A secure hierarchical model for sensor network

Wireless Sensor-Based Traffic Light Control

Multi-level transaction model for semantic concurrency control in linear hash structures