Entities In Physical World Research Articles

Data aggregation scheme for IOT based wireless sensor network through optimal clustering method

Wireless sensor network (WSN)based Internet of Things (IoT) has gained much popularity, in offering solutions to several real-time applications by interaction between sensor nodes and physical world entities through interconnected technology. WSN based IoT has become key technology in achieving real-time quality of service (QoS), low-cost operation and long-term reliability. IoT based WSN nodes, permits interconnection of various objects wirelessly and these nodes are tiny, equipped with irreplaceable battery and are resource constrain. Due to continuous sensing and gathering, IoT produce huge volume of data which may results in high computation overhead, data redundancy, packet collision and high energy consumption. To address resource constrains, significant research has been conducted to optimize energy consumption of nodes to extend network lifetime. Most of the existing methods focus on extending network lifetime by scheduling method through duty cycles, however these methods fails to handle data redundancy and has lower throughput. Cluster based data aggregation schemes have offered solution to eliminate data redundancy and harvest energy. In this paper we propose an efficient data aggregation scheme (EDAS) for IoT based WSN, this scheme considers improved low energy adaptive clustering algorithm (I-LEACH) to form optimal number of cluster head (CH), by considering node residual energy and average network energy. Data redundancy is eliminated using network coding, this technique integrates liner XOR operation and ensures non-replicated data transmissions. Finally, we performed simulations of proposed EDAS scheme to evaluate network parameters and performance of EDAS is compared with existing schemes.

Joint Data Sampling and Link Scheduling for Age Minimization in Multihop Cyber-Physical Systems

In cyber-physical system (CPS), sensor-based communication components are widely deployed to monitor real-time physical phenomena and send the information to network to enable control of entities in physical world. The freshness of data is of critical importance in such systems. Age of information (AoI) is a performance metric which measures data freshness at the destination since the last sampling at the data source. In this letter, we consider a multihop CPS with multiple data flows and investigate an age minimization problem by jointly optimizing data sampling at the sources and link scheduling along the path of each data flow. The formulated problem falls in the form of an integer nonlinear program. To solve the problem efficiently, we propose a light-weight scheduling algorithm. Compared with traditional delay-based scheduling scheme, simulation results show that AoI-based scheduling scheme performs better in delivering information in a timely manner. Moreover, we demonstrate that by jointly optimizing link scheduling and sampling time, network-level data freshness can be further improved.

Energy-Aware Real-Time Data Processing for IoT Systems

In many real-time processing systems for the Internet of Things (IoT), the correctness of real-time data objects that model physical world entities, such as the status of mobile robotics, depends not only on the functional correctness, but also on the temporal consistency. Maintaining temporal consistency of real-time data while reducing energy cost is of critical importance when designing such IoT systems. In this paper, we formulate the energy-aware real-time data processing problem on multicore platforms and prove it to be NP-hard. In view of the intractability of the problem, we adopt a divide-and-conquer strategy. We first propose a per-CPU solution, which can result in significant power savings. Next, in order to save energy in a fine-grained granularity, we propose an efficient per-Task solution by adopting the per-CPU solution as a building block. Finally, by developing new energy-aware mapping techniques, we further explore energy savings on multicore platforms. Extensive simulation results show that the proposed methods offer remarkable performance improvement in terms of energy savings, as compared to the state-of-the-art schemes.

Dynamic Verification of Mashups of Service-Oriented Things through a Mediation Platform

The new Internet is evolving into the vision of the Internet of Things, where physical world entities are integrated into virtual world things. Things are expected to become active participants in business, information and social processes. Then, the Internet of Things could benefit from the Web Service architecture like today's Web does; so Future service-oriented Internet things will offer their functionality via service-enabled interfaces. As demonstrated in previous work, there is a need of considering the behaviour of things to develop applications in a more rigorous way. We proposed a lightweight model for representing such behaviour based on the service-oriented paradigm and extending the standard DPWS profile to specify the (partial) order with which things can receive messages. To check whether a mashup of things respects the behaviour, specified at design-time, of composed things, we proposed a static verification. However, at run-time a thing may change its behaviour or receive requests from instances of different mashups. Then, it is required to check and detect dynamically possible invalid invocations provoked by the behaviour's changes. In this work, we extend our static verification with an approach based on mediation techniques and complex event processing to detect and inhibit invalid invocations, checking that things only receive requests compatible with their behaviour. The solution automatically generates the required elements to perform run-time validation of invocations, and it may be extended to validate other issues. Here, we have also dealt with quality of service and temporal restrictions.

Enhancing Security in Cyber Physical Systems through Policy based Trust Management against Deception Attack

The World is moving towards invisible computers, Ubiquitous Computing (any information everywhere), Pervasive Computing (which combines current network technology with wireless computing), Ambient Intelligence (which refers to electronic environments that are sensitive and responsive to the presence of people), and Traditional Embedded System (which is a closed system, not only in the sense of closed physical locations or dedicated hardware, but also closed with respect to the boundaries, where CPS (Cyber Physical Systems) is an open system which integrate computing and communication with monitoring and/or control of entities in physical world. CPS is the integration of several Wireless Sensor Networks.CPS is used in several applications like Automotive electronics, Avionics, Medical systems, Forestry machines, Logistics, Autonomous Vehicles, and Smart Structures. These are all “Critical Systems”, the failure of the system will harm the people who depend on it. Some challenges in CPS are low power, no standard interface of sensors, low cost and high accuracy terminal devices and security. A system without security is like bank without locks. “Trust Management” plays an important role in security of CPS, since it is an open system. Trust Management is a dynamic concept which changes depending on the application. Trust is related to the authentication, authorization which comes under the hard side of trust. And also competence, reliability, integrity, timeliness, accuracy which comes under soft side of trust. Secured data or information can be trusted. This paper mainly focuses on the trustworthiness of a sensor and controller, where the trust depends on the reliability of the data sent by them. The Policy Based Trust Management is used to identify the false information sent from sensors/controllers by calculating the weight-age of the data integrity. This ensures the truthfulness of the sensor/controller in the CPS.