Search

Clustering is the approach, which is utilized for aggregating the nodes as a group called clusters, which is used for reducing the routing overheads. This is a fundamental approach to extend the life expectancy of Wireless Sensor Network. However, the main challenge in WSN is the cluster head selection while taking the energy stabilization into account. Optimization within the WSN is the outstanding concern to provide intellect for the extensive period of network lifetime. Since clustering is a topological control method to decrease the process of SNs, it extensively improves overall system scalability and energy efficiency. Moreover, the appropriate selection of CH plays crucial role for attaining sustainable WSN. This paper proposes the firefly contribution with Firefly Cyclic Randomization (FCR) for the selection of cluster head in WSN. The randomly created solution in this algorithm is found based on three distribution functions like Uniform, Normal, and Gamma distributions. Moreover, the analysis is made on the second algorithm Firefly Cyclic Grey Wolf Optimization (FCGWO) by modifying $$r^{1}$$ and $$r^{2}$$ (random vectors) of Grey Wolf Optimization. In reality, the FCR and FGCGWO algorithms are planned on selecting the optimal cluster head by concentrating mainly on minimization of delay, minimization of the distance between nodes, and stabilization of energy. The analysis is performed and explained in terms of alive nodes, network lifetime, and energy efficiency under the three distributions.

Background: Number of resource allocation and bidding schemes had been enormously arrived for on demand supply scheme of cloud services. But accessing and presenting the Cloud services depending on the reputation would not produce fair result in cloud computing. Since the cloud users not only looking for the efficient services but in major they look towards the cost. So here there is a way of introducing the bidding option system that includes efficient user centric behavior analysis model to render the cloud services and resource allocation with low cost. Objective: The allocation of resources is not flexible and dynamic for the users in the recent days. This gave me the key idea and generated as a problem statement for my proposed work. Methods: An online auction framework that ensures multi bidding mechanism which utilizes user centric behavioral analysis to produce the efficient and reliable usage of cloud resources according to the user choice. Results: we implement Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis. Thus the algorithm is implemented and system is designed in such a way to provide better allocation of cloud resources which ensures bidding and user behavior. Conclusion: Thus the algorithm Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis is implemented & system is designed in such a way to provide better allocation of cloud resources which ensures bidding, user behavior. The user bid data is trained accordingly such that to produce efficient resource utilization. Further the work can be taken towards data analytics and prediction of user behavior while allocating the cloud resources.

This paper introduces an algorithm, termed self-adaptive genetic grey wolf optimizer (self-adaptive genetic GWO), for privacy preservation using a C-mixture factor. The C-mixture factor improves the privacy of data, in which the data does not satisfy the privacy constraints, such as l-diversity, m-privacy, and k-anonymity. Experimentation is carried out using the adult dataset, and the effectiveness of the proposed self-adaptive genetic GWO is checked depending on the information loss and the average equivalence class metric values and is evaluated to be the best when compared to other existing techniques with low information loss value as 0.1724 and average equivalence class value as 0.71, respectively.

Data stream classification plays a vital role in data mining techniques which extracts the most important patterns from the real world database. Nowadays, many applications like sensor network, video surveillance and network traffic generate a huge amount of data streams. Due to the ambiguity in input data, imprecise input information and concept drift, some problems arise in classifying the data stream. To resolve these problems, we propose a HRNeuro fuzzy system in this paper based on rough set theory and holoentropy function. At first, the input database is given to the PCA algorithm to reduce the dimension of the data. An adaptive neuro fuzzy classifier is utilized where the designing of membership function and rule base are the two important aspects. Then, neuro-fuzzy system undergoes updating when the change of detection occurs between the data streams. Here, the updating behaviour of membership function and rules are performed using rough set theory and holoentropy function. The experimental results are evaluated for the datasets and the performance is analysed by some metrics and compared with the existing systems such as JIT adaptive K-NN and HRFuzzy system. From the result, it is concluded that our proposed fuzzy classifier attains the higher accuracy of 96% which proves the efficient performance of data stream classification algorithm. Keywords: Data stream, Neuro fuzzy, Change of detection, Rough set theory, Holoentropy function

Due to increasing need of using distributed databases, high demand presents on sharing data to easily update and access the useful information without any interruption. The sharing of distributed databases causes a serious issue of securing information since the databases consist of sensitive personal information. To preserve the sensitive information and at the same time, releasing the useful information, a significant effort is made by the researchers under privacy preserving data publishing that have been receiving considerable attention in recent years. In this work, a new privacy measure, called c-mixture is introduced to maintain the privacy constraint without affecting utility of the database. In order to apply the proposed privacy measure to privacy preserving data publishing, a new algorithm called, CPGEN is developed using genetic algorithm and multi-objective constraints. The proposed multi-objective optimization considered the multiple privacy constraints along with the utility measurement to measure the importance. Also, the proposed CPGEN is adapted to handle the cold-start problem which commonly happened in distributed databases. The proposed algorithm is experimented with adult dataset and quantitative performance is analyzed using generalized information loss and average equivalence class size metric. From the experimentation, we proved that the proposed algorithm maintained the privacy and utility as compared with the existing algorithm. Keywords: Privacy, Utility, Distributed databases, Data publishing, Optimization, Sensitive information

Internet of Things (IoT) has been a most important research area for almost a decade now, where a huge network of billions or trillions of “things” communicating with one another is facing many technical and application challenges. Although there are many uncertainties about its security and privacy, the literature presents different techniques to handle the security issues and challenges in order to develop a well-defined security architecture. This paper reviews 50 research papers that are related to the security of IoT. The security techniques were classified with respect to time consumption, energy consumption, power consumption, lightweight property, reliability, robustness, and smart applicability. Also, the security techniques were analyzed based on the considered attacks, application, utilized simulation tool, security model, and attributes. The objective of the survey is focused on the security loopholes arising out of the information exchange technologies used in IoT. Finally, the important research issues are addressed for the researchers to find the way for further research in the security of IoT. The survey signifies that multilevel and mutual authentication based on attribute-based profile modeling bring more security for access control and authentication.

The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is considered a vital process. The data analysis process consists of different tasks, among which the data stream classification approaches face more challenges than the other commonly used techniques. Even though the classification is a continuous process, it requires a design that can adapt the classification model so as to adjust the concept change or the boundary change between the classes. Hence, we design a novel fuzzy classifier known as THRFuzzy to classify new incoming data streams. Rough set theory along with tangential holoentropy function helps in the designing the dynamic classification model. The classification approach uses kernel fuzzy c-means (FCM) clustering for the generation of the rules and tangential holoentropy function to update the membership function. The performance of the proposed THRFuzzy method is verified using three datasets, namely skin segmentation, localization, and breast cancer datasets, and the evaluated metrics, accuracy and time, comparing its performance with HRFuzzy and adaptive k-NN classifiers. The experimental results conclude that THRFuzzy classifier shows better classification results providing a maximum accuracy consuming a minimal time than the existing classifiers.

Wireless sensor network (WSN) is comprised of tiny, cheap and power-efficient sensor nodes which effectively transmit data to the base station. The main challenge of WSN is the distance, energy and time delay. The power resource of the sensor node is a non-rechargeable battery. Here the greater the distance between the nodes, higher the energy consumption. For having the effective transmission of data with less energy, the cluster-head approach is used. It is well known that the time delay is directly proportional to the distance between the nodes and the base station. The cluster head is selected in such a way that it is spatially closer enough to the base station as well as the sensor nodes. So, the time delay can be substantially reduced. This, in turn, the transmission speed of the data packets can be increased. Firefly algorithm is developed for maximizing the energy efficiency of network and lifetime of nodes by selecting the cluster head optimally. In this paper firefly with cyclic randomization is proposed for selecting the best cluster head. The network performance is increased in this method when compared to the other conventional algorithms.

Background/Objectives: The working of TCP upon Wireless Networks is the most difficult issue, as a result of arbitrary misfortunes and ACK impedance. TCP likewise experiences execution declination as far as making postponement and overhead in system due to the poor attributes of the Wireless channel. Keeping in mind the end goal is to beat these issues and to enhance the performance of TCP in MANETs. Methods/Statistical Analysis: The Congestion Control in Multi - Hop Mobile Ad - Hoc Networks Using Cross - Layer Based TCP Protocol Approach, the mechanism triggers congestion whenever the Channel Occupied Ratio (COR) reaches a maximum threshold value and the received signal strength is less than a minimum threshold value. Following it, congestion control scheme controls the data sending rate of the sender by determining the available bandwidth, delay of its link and COR. Further, a fair resource allocation scheme is put forwarded. Findings: A Smart Acknowledgment Distributed Channel Access (SADCA) is proposed, where a different Access Category (AC) for data less TCP acknowledgement packets is utilized and after that it is relegated with the highest priority. Along these lines, the postponement amid the transmission of packet can be lessened and furthermore the affirmation for the packet can be sent instantly. Keeping in mind the end goal to increase the performance of TCP, delay window size can likewise be balanced by considering the parameters, for example, transmission rate, number of jumps, and Channel Occupied Ratio (COR). Thus, the proposed plan helps in staying away from any sort of postponement and overhead to send the TCP acknowledgements. Applications/Improvements: The delay during the transmission of packet is decreased and the packet is recognized instantly. To expand the performance, the delay window size can be balanced for improvement purpose by considering the parameters, for example, transmission rate, number of jumps, and COR. The proposed scheme improves delay and overhead to send TCP acknowledgement.

Mobile Ad-hoc Networks (MANETs) are expected to play an important role in military networks by providing infrastructure less communication. However, maintaining secure and instant information sharing is a difficult task especially for highly dynamic military MANETs. Different solution proposed for scaling own the large size of military ad hoc network, one of the most intrinsic approaches is clustering techniques which evolved an important role in military mobile ad hoc networks. Clustering can be used for load balancing to extend the lifetime of ad hoc network by reducing energy consumption and increase network scalability. And the cluster one node works as a cluster head and coordinates all the activities such as routing. In this study, an Improved Load Balanced Connection Aware (ILBCA) clustering hierarchy protocol is presented for MANET that leads to cluster formation in military application. The protocol launches two consecutive phases called setup and steady-state. In setup phase, cluster heads and relay nodes as well as the path between member node from cluster and cluster head are determined. In steady-state phase, network data is collected from member nodes and transmitted to cluster head according to the topology which is determined in the same round. Simulated tests indicate that the ILBCA clustering hierarchy protocol can build more balanceable clustering structure, enhance the network life cycle and energy efficiency.

Objectives: MANET has access to excess of real-time data in today’s modern military applications. A portion of military Internet protocol network has a number of challenging task to attain the quality of service to achieve load balancing and energy efficiency. The backhaul radio connected with routing protocol to create a network node doesn’t consider the load balancing problem. Methods: This paper proposes an improved Load Balanced Distributed Weight-based Energy-efficient Clustering (LBDWEC) hierarchy routing protocol algorithm for load balancing in cluster based MANET. A hierarchical routing path is tracked and stored in the cluster heads instead of the network nodes. Thus the routing overheads are reduced effectively. The performance of the Cluster Head (CH) in an unhinged and a non-reliable state degrades the network performance since the cluster head plays a dominant role in routing and tracing of messages between the source and the destination. Selecting a prominent cluster head is based on the electing and priority basis. The formation of a cluster results in three different levels like cluster head, strong and the weak nodes. The differentiation of stronger and weaker node is based on the evaluation of the network density, residual energy and transmission of data between source and destination. A multi agent routing based algorithm is generated to make a possible load balanced route between the source and the destination in the cluster supported network. Findings: A load balanced scheme is presented in this paper to achieve energy efficiency considering both energy usage and congestion amongst the network. The threshold value is accounted here to evaluate the overloading intermediate node with crisis to the queue length across the path. The proposed LBDWEC hierarchy routing protocol uses an optimal path to calculate the energy usage. The algorithm shows better results in achieving the throughput, message delivery ratio and energy efficiency with respective to load balancing in the clustering network.

Routing in Wireless Sensor Networks (WSNs) plays a significant role in the field of environment-oriented monitoring, traffic monitoring, etc. Here, wide contributions that are made toward routing in WSN are explored. The paper mainly aims to categorize the routing problems and examines the routing-related optimization problems. For achieving the motive, 50 papers from the standard journals are collected and primarily reviewed in a chronological way. Later, various features that are related to energy, security, speed and reliability problems of routing are discussed. Subsequently, the literature is analyzed based on the simulation environment and experimental setup, awareness over the Quality of Service (QoS) and the deployment against various applications. In addition, the optimization of the routing algorithms and the meta-heuristic study of routing optimization are explored. Routing is a vast area with numerous unsolved issues and hence, various research gaps along with future directions are also presented.

Broodstock of the John’s snapper Lutjanus johnii were raised in sea cages from wild collected juveniles of the species. Individual fishes were tagged using passive integrated transponders (PIT), cannulated and gonadal biopsies were examined periodically for assessing the maturity status. The matured fishes were shifted from cages and maintained in indoor FRP tanks. Females were given two doses of human chorionic gonadotropin (hCG) and ovaprim @ 800 - 900 IU kg-1 and 1.25ml kg-1 respectively. Males were given only hCG in a range between 400 and 600 IU kg-1. Two successful spawning were obtained with 80-85% fertilisation rate. In both the trials, embryonic development was observed to be arrested before hatching which could be attributed to nutritional deficiency of the broodfishes and high water temperature in the spawning tank.

TCP allows sharing the information about network status using Cross Layer mechanism for the different layers. The Cross Layer approach in wireless MANETs is provided for improving TCP performance. The Optimal Path or Route Selection is an important aspect for increasing energy efficiency and lifetime of the network. A proposal for Trust Aware Routing protocol is described for selecting an optimal route in MANETs. Direct and Indirect trust values are used for estimating the trust value of every node in the network. The route cost amount is estimated and the best path with minimum cost value is chosen for the network. The data packet is transmitted on the optimal path, and the optimal path is selected on the minimum cost value of the network. There is a possibility of the packets being dropped due to congestion and / or mobility and there are chances of the packets being reordered during the transmission process. Reorder Identification mechanism is the procedure used for dropped and / or reordered packets. The simulation results of the proposed work are compared with the existing work and it shows more effective in terms of energy efficiency and network lifetime.

Emergency Call Alert (ECA) Application is developed for inform the urgency as well as seriousness of the call to the receiver. The profile in the mobile facilitates that the user to change the mode they need and this requires manual work load. This Call Manager changes the pro-file automatically to the desired mode designed by the user. It has also been enhanced with filtering mechanism called as Emergency calls filter which allows the calls from the emergency list to be in user preferred mode irrespective of the current mode. This feature is to avoid the missing of calls from the numbers specified in the emergency call list. Now a day most of calls come to us when we are busy, it is an interrupt, which disturbs or sometimes accident may happen. To avoid this either we switch off the mobile or we put the mobile in silent mode. If this is so if any emergency call comes we cannot attend such type of calls. The other disadvantage of this is the calling person does not know when the called person is free. To overcome all these problems we presented paper, Emergency Call Manager which handles all the call when he/she is busy sends an SMS. Software which filters this message and it gives an emergency alarm to called mobile.

Pueruli and post‐pueruli, early juveniles and sub‐adults of the spiny lobster, Panulirus homarus and juveniles of P. ornatus were grown in different floating sea cages along the southeast coast of India from May 2003 to May 2007. The first type of cage had a galvanised iron pipe frame (2.0 m × 2.0 m × 1.2 m) with steel woven mesh and four inner detachable compartments (0.75 m × 0.75 m × 1.10 m). Fibre‐reinforced plastic was used subsequently to fabricate cages (1 m × 1 m × 1 m). Pueruli and post‐pueruli of P. homarus (1.58 ± 0.62 g SD), stocked at 60 individuals/m2, grew to an average weight of 123.10 ± 26.22 g in 266 days with a survival rate of 70%. Sub‐adults of P. homarus with an average weight (± SD) of 123.61 ± 29.26 g reached 341.25 ± 46.22 g in 225 days at a stocking density of 21 individuals/m2 with a survival of 73 ± 6%. The post‐pueruli grew by 0.46 ± 0.10 g per day with a specific growth rate (SGR) of 1.64, whereas sub‐adults had a growth rate of 0.97 ± 0.20 g per day with a SGR of 0....

The scyllarinid lobster, Petrarctus rugosus was reared to the postlarval nisto in 51 days at 24.9–26.5°C between November 2003 and April 2004 in Chennai, India. The lobster had eight phyllosomal instars. The eighth instars died while moulting to nisto. Instar VI was attained in 34 days with an average intermoult period of 5.4 days, whereas the last two moults took 17 days to complete. The captive breeders mated and bred several times between November and April with peak spawning in February. Repetitive breeding was observed with the brooding period varying from 11 to 17 days. Mean fecundity was 17 004 eggs ± 11 486 (SD). Hatching percentage was between 0.00 and 87.44.

Captive broodstock of the spiny lobster, Panulirus homarus, mated successfully and produced more than 105 spawnings over 4 years. Improvements in nutrition and rearing conditions increased the number of spawnings from less than 2, to 4 per year. A single breeder mates three or more times in a year and may spawn more than once following a single mating. An average of four repetitive spawnings per year was recorded. One third of the females spawned 5 times and a single female spawned 7 times in one year. The phyllosoma were released in one or two batches on successive days. The number of phyllosoma larvae released varied from 16 000 to 529 180 with breeder weights ranging from 218 to 696 g.

A pair of subadult Panulirus ornatus was reared in the laboratory from July 2001. The female grew from 0.6 to 1.3 kg and the male from 0.5 to 1.6 kg in 2 years before the first mating in July 2003. In 6 months, from July to December 2003, the pair mated and spawned 3 times, producing 1.6 million eggs and 1.1 million phyllosoma larvae. Mating occurred 25 and 63 days after moulting. The female spawned 2–3 days after mating and the incubation time ranged from 23 to 27 days. The phyllosoma larvae were released over 2 successive days. The growth rate reduced after first mating in both the male and female and the female expended 42% of the total weight gain for egg production.