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This paper proposes a novel improved polar bear optimization (IPBO) algorithm and employs it along with polar bear optimization (PBO) and chaotic population-based variants of polar bear optimization algorithm to solve combined economic emission dispatch (CEED) problem. PBO is a meta-heuristic technique inspired by the hunting mechanisms of polar bears in harsh arctic regions based only on their sense of sight. Polar bears in nature exhibits hunting of prey not only on their sight but also on their keen sense of smell. Hence, a novel improved variant of PBO which enhances its operation by equipping it with tracking capabilities utilizing polar bears sense of smell has been proposed in this study. The validity of novel IPBO is tested through 5 benchmark functions and 140 units Korean ED problem. Furthermore, the impact of different population initialization methods is also observed on the capabilities of conventional PBO. The proposed chaotic population based PBO, improved PBO (IPBO) and PBO are employed to solve IEEE 3 unit and 6-unit CEED problem. CEED is a multi-objective power system optimization problem with conflicting objectives of cost and emission. The simulations performed undertake each objective individually as well as collectively. The results achieved by each technique are analyzed statistically through Wilcoxon rank sum test (WRST), probability density function and cumulative density function. Both the statistical and numerical analysis of results showcase the strength of each solution technique as well as their ability to improve cost and emissions in the solution of CEED problem.

This article presents multiple strategies to handle ramp rate in dynamic economic load dispatch (DELD) problem. DELD is a power system optimization problem that tackles the dispatch of thermal gene...

Nowadays, both the modern and developing countries are planning to deploy Internet of Vehicles for smart transportation systems to face the traffic congestion problems. Shifting from current road conditions to smart ones is a real challenge where all the vehicles and road infrastructure are not equipped with wireless network interfaces. The urban environment is more congested than highway scenarios and has more issues of delay and travel time. Various types of route suggestion protocols have been proposed where most of them consider smart vehicles which are equipped with smart and intelligent communication devices. The most of existing schemes have not considered non-equipped vehicles which have a major cause of traffic congestion. This paper presents a route suggestion protocol to suggest an optimal congestion aware route in the network. Equipped and non-equipped vehicles are taking into account for congestion index formulation along with driving distraction factors. Simulation results indicated the greater performance of proposed protocol and reduce the travel time effectively when works with IoV as compared to traditional route suggestion protocols.

In this paper Economic Dispatch (ED) problem is solved by a novel Quasi population-based variant of Polar Bear Optimization (QPBO) algorithm. This algorithm is applied to solve both convex and non-convex systems. PBO is a nature inspired meta heuristic optimization algorithm having inherent strengths of population-based strategies. Like all population-based approaches PBO achieves near optimum results. Enhancing the working of PBO with quasi population strategy is expected to improve its global convergence rate. The effectiveness of QPBO is tested on four IEEE test systems and the results obtained are compared with other techniques already available in literature. Comparison of results proved QPBO success in reducing cost and at a better convergence rate as compared to other techniques.

In this paper Dragonfly Algorithm (DA) is employed to solve Dynamic Economic Dispatch (DED) problem. DED is a highly non-linear, non-convex and multi dimensional power system optimization problem. DA is a nature inspired meta- heuristic technique inspired by static and dynamic swarming behaviors of dragonflies. In this paper DA is employed to solve IEEE 5-unit test system under valve point effect including losses. Results of simulations show improvement in cost and execution time proving validity of proposed techniques in solution of DED problem.

An organization is a combination of vision, technology and employees. The wellbeing of organization is directly associated with the honesty of its workers. However, an organization is also threatened by misuse of information from its agents like former employees, current employees, vendors or business associates. These kinds of threats which are posed from within the organization are known as Insider Threats. Many approaches have been employed to detect the Insider Threats in organizations. One of such approaches is to monitor the system functions to detect possible insiders. These approaches raise unnecessary amount of false positive alarm which is then taken care of with the use of evolutionary algorithms. The solution to this Insider Threat detection requires a lot of configuration before implementation in real world scenarios due to different threshold values in different organizations. Insider Threat detection can be done by means of honeypots sensors in a limited and in satisfactory way. The present research proposes a new technique for detecting insiders using encrypted honeypots. This technique complements the existing insider detection systems and improves its performance in terms of decreasing false positive results.

With the advancement in technology, the size of electronic components and printed circuit boards (PCB) is becoming small while the pin count of each component is increasing. This has necessitated the use of ball grid array (BGA) type of components where pins are attached under the body of component as a grid. The problem of routing pins from under the body of component to the boundary of the component is known as escape routing. It is often desirable to perform ordered simultaneous escape routing (SER) to facilitate area routing and produce elegant PCB design. The task of SER is non-trivial, given the small size of components and hundreds of pins arranged in random order in each component that needs ordered connectivity. In this paper, first we propose flow models for different inter pin capacities. We then propose linear network flow optimization model that simultaneously solves the net ordering and net escape problem. The model routes maximum possible nets between two components of the PCB, by considering the design rules. Comparative analysis shows that the proposed optimization model performs better than the existing routing algorithms in terms of number of nets routed.

Modern wireless communication technologies enabled high data rate support which stands in need of proficient MAC protocols. In WLANs, the fair channel access and collision avoidance are achieved by employing contention. The contention period degrades bandwidth utilization and longer delays; the network performance worsens for high data rates. Previously, this problem is addressed by modifying or adaptively selecting contention time using the same time-domain- based backoff mechanism. In this paper, we propose a backoff scheme, FD-Backoff, in which backoff is taken in the frequency domain. Therein, an integer is assigned to every data subcarrier, and then, a random data subcarrier (integer) is chosen to transmit a RTS packet. Since OFDM-based data subcarriers are orthogonal, thus simultaneous transmission of multiple RTS packets is possible. Every nontransmitter node listens on the whole channel bandwidth to observe any active subcarriers. The transmitter who chose smallest subcarrier for RTS transmission wins channel access and receiver replies it with a CTS packet. Contrary to the IEEE 802.11 backoff mechanism, the proposed backoff scheme offers lesser and relatively fixed contention overhead. Performance analysis based on analytical and simulation study suggests that the proposed scheme promises lower contention overhead and higher efficiency gain (up to 35 %) as compared to standard channel access mechanism.

A b s t r a c t Power system operation with proper planning is an utmost task for enhancing the economy of the country. The Optimal Reactive Power Dispatch (ORPD) plays an important task for secure, reliable and optimal operations of power system. ORPD is a complex, non-linear, non-convex, non-continuous and multi-model problem which involves discrete as well as continuous variables. Thus, its solution comprises of different objective functions like improving voltage profile, reducing power losses, voltage stability enhancement and transmission cost minimization. Due to the non-linear nature of problem, most of the techniques applied to ORPD are meta-heuristic. Despite the numerous articles published on these techniques, none has given sufficient emphasis on the comprehensively summarizing the existing meta-heuristic methods for solution of ORPD problem. This work presents a survey of different meta-heuristic techniques applied for solution of ORPD problems in power transmission system. Moreover, a new meta-heuristic Sine-Cosine algorithm is also proposed to solve the problem. A case study is performed where different meta-heuristic techniques are implemented to solve the same problem. Later, statistical analysis is performed to rank all implemented techniques. It is envisaged that the information gathered in this paper will be a valuable one-stop source of information for researchers working on this topic.

With the advancement in electronics technology, number of pins under the ball grid array (BGA) are increasing on reduced size components. In small size components, a challenging task is to solve the escape routing problem where BGA pins escape towards the component boundary. It is often desirable to perform ordered simultaneous escape routing (SER) to facilitate area routing and produce elegant Printed Circuit Board (PCB) design. Some heuristic techniques help in finding the PCB routing solution for SER but for larger problems these are time consuming and produce sub-optimal results. This work propose solution which divides the problem into two parts. First, a novel net ordering algorithm for SER using network theoretic approach and then linear optimization model for single component ordered escape routing has been proposed. The model routes maximum possible nets between two components of the PCB by considering the design rules based on the given net ordering. Comparative analysis shows that the proposed net ordering algorithm and optimization model performs better than the existing routing algorithms for SER in terms of number of nets routed. Also the running time using proposed algorithm reduces to O(2NE=2) + O(2NE=2) for ordered escape routing of both components. This time is much lesser than O(2NE) due to exponential reduction.

With the advancement in technology, BGA based integrated circuits for robotics and other devices are being prepared in small sizes with more pin count. This increase in number requires more number of pins to be escaped from the inner side of the IC towards the escape boundary. Ordered escape routing is very important due to its great impact on area and length routing at later stage. Basic design rules of planarity and capacity along with constraints like length matching make the ordered escape routing problem more difficult. In this paper we formulate flow model on the basis of inter-pin capacity. Using flow model we propose optimization model that solves ordered escape routing problem under design constraints. Evaluation of model using randomly generated examples shows that maximum possible nets are being routed by the model.

Cognitive radio improves spectrum utilization by allowing secondary users to transmit on vacant spectrum band allocated to licensed users without affecting their activity on that spectrum. Cognitive radio address the problem of spectrum inefficiency as well as spectrum scarcity but it's quite challenging to capture the volatile spectral nature of cognitive radio environment using single transceiver. This work proposes an optimization model for combined spectrum decision and routing in single transceiver cognitive radio networks for maximizing overall network capacity. Proposed centralized algorithm ensures some minimum throughput for all flows in the network using fairness ratio and maximizes this ratio to increase the overall network capacity. Proposed model considers channel heterogeneity which is a critical aspect in making efficient spectrum decision and selects optimal route based on primary user's activity and application requirements of the cognitive users. Results show that proposed optimization model increases the overall network capacity by maximizing fairness ratio for all the flows in the network and is quite comparable with the existing multipath routing models for cognitive radio network and performs better in case of random topology.

With the growth of internet people are shifting from their paper based news system to online news system. These online news websites are very useful for the people who have internet access and they can easily read and search their required news through home/office computer or cell phone without wasting their time. To search a particular news, many searching algorithms and News Fetching Systems (NFS) are available which return the results in less than a second. But how much correct information they are giving from a huge data is still a critical area, where we need some efficient algorithms to give us more optimized results. We propose a Multiple Leaf Nodes based Parse Trees for NFS where all the leaf nodes are commonly used alternative words for a specific word. We evaluate our results for a randomly selected webpage and compare with the simple parse tree system. Analysis shows that our proposed algorithm can enhance the performance of any NFS.

Wireless Mesh Networks play an important role in the next production wireless communication systems as it can support broadband services with omnipresent coverage and low transmission power with high capacity and high processing power. The efficiency of mesh networks is further improved by a routing path determination mechanism that considers most of the causes of transmissions failures. Our proposed routing metric takes into account transmissions failures by considering the backoff mechanism used in IEEE 802.11 networks and assign weights to each path. These weights act as a metric in route selection among different paths. The proposed scheme further utilizes this metric to provide load balancing. Consequently this metric helps the routing protocols to balance traffic and avoids traffic through congested paths.