International Journal of Sensors Wireless Communications and Control - Volume 5, Issue 2, 2015

This paper addresses event-based control design problem for discretetime linear systems subject to input and state constraints with guaranteed performance measured by an assigned quadratic cost function. Instead of considering a model-predictive controller (MPC) and a given event-triggering condition as usually proposed in literature, a codesign problem of the control parameters and the event-triggering parameters is formulated as a linear matrix inequality optimization problem with the objective of maximizing the domain of attraction. The effectiveness of the proposed codesign strategy is evaluated for networked control of an inverted pendulum mounted on a cart and compared with an existing event-based MPC strategy in literature.

This paper investigates the problem of event-based consensus of discretetime multi-agent systems with general linear dynamics subject to actuator saturation. Leader-following and leaderless semi-global consensus are achieved by a distributed event-trigger strategy for the multi-agent systems. In spite of the input saturation constraint, it is shown that feedback control updating is unnecessary until an event is triggered. The combinational-state variables and the Riccati equation are used to construct a Lyapunov function and to design the event-triggering conditions and the low-gain control laws. Numerical examples are provided to illustrate the theoretical results.

This paper is concerned with an event triggered distributed optimization algorithm for network utility maximization (NUM) problems. According to an event triggering logic, a source broadcasts its information to links when a local signal exceeds a state dependent threshold. A similar communication logic is executed by each link, where the link broadcasts its information to all sources that use the link. The algorithm is based on a sequential barrier method, which can be applied to optimization problems with constraints. The efficiency of the proposed scheme is verified via simulations. The simulation result shows that the proposed algorithm reduces the number of message exchanges while guaranteeing the converge to the optimal solution.

Devices for Wireless Sensor Networks (WSN) are limited by power and thus routing protocols should be designed with this constrain in mind. This paper presents and evaluates an Energy Efficient Position Based Adaptive Real-Time Routing protocol (EFPBARP) as a novel, real-time, position based and energy efficient routing protocol. EFPBARP is a lightweight protocol that reduces the number of nodes which receive the RF signal using a novel Parent Forwarding Region (PFR) algorithm. EFPBARP as a Geographical Routing Protocol (GRP) reduces the number of forwarding nodes and thus the traffic and packet collision in the network. A series of performance evaluations through Matlab and Omnet++ simulations show significant improvements in network performance parameters and total energy consumption over CTP and Directed Flooding Routing Protocol (DFRP).

One of the scarcest resources in wireless sensor networks (WSNs) is energy. Thus, a major issue of WSN is to prolong the network lifetime. The energy dissipation of sensor nodes should be minimized within the network for prolong network lifetime. For the sake of this, data aggregation emerged as an important field of research in modern era. Intensive research has been carried out for providing novel energy efficient and secure data aggregation techniques. Unlike conventional data aggregation techniques, polynomial regression based data aggregation technique increases the network lifetime by transmitting compressed data packets of constant size. Data compression has been carried out by performing regression function on the sensed data. These techniques provide good approximation of the sensed value and are scalable as the data compression ratio is nearly constant. In this paper, we present a detailed review on different polynomial regression based data aggregation techniques and provide a comparison among them.

Wireless Sensor Networks (WSNs) are more vigorously being used with applications relating to the Internet of Things (IoT). They are used for a variety of applications, but are frequently deployed keeping in view a specific objective. Sensor network virtualization may be classified as network and sensor virtualization. Virtualization comes with numerous challenges in the form of segregating various networks, hardware and associated software in the system. This research paper touches upon the past and current research directions associated with virtualization, various design targets, layouts and numerous testbeds have also been looked into. The paper also highlights the current challenges and future avenues associated to expedite research on virtualization.