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This paper presents priority-first packet scheduling approach for heterogeneous traffic flows in low data rate heterogeneous wireless sensor networks (HWSNs). A delay sensitive or emergency event occurrence demands the data delivery on the priority basis over regular monitoring sensing applications. In addition, handling sudden multi-event data and achieving their reliability requirements distinctly becomes the challenge and necessity in the critical situations. To address this problem, this paper presents distributed approach of managing data transmission for simultaneous traffic flows over multi-hop topology, which reduces the load of a sink node; and helps to make a life of the network prolong. For this reason, heterogeneous traffic flows algorithm (CHTF) algorithm classifies the each incoming packets either from source nodes or downstream hop node based on the packet priority and stores them into the respective queues. The PFPS-EDF and PFPS-FCFS algorithms present scheduling for each data packets using priority weight. Furthermore, reporting rate is timely updated based on the queue level considering their fairness index and processing rate. The reported work in this paper is validated in ns2 (ns2.32 allinone) simulator by putting the network into each distinct cases for validation of presented work and real time TestBed. The protocol evaluation presents that the distributed queue-based PFPS scheduling mechanism works efficiently using CSMA/CA MAC protocol of the IEEE 802.15.4 sensor networks.

In recent years, peer-to-peer (P2P) network has reached popularity in file sharing as it is a distributed and decentralized network architecture. As there is no centralized authority, there arise various attacks, which lead to insecurity in the network. Thus, the security issues of the P2P networks are to be considered with more care. This paper proposes an authentication and authorization approach, named fuzzy enabled advanced encryption standard (AES)-based multi-level authentication and authorization to offer security against various kinds of attacks that occur in the P2P networks. Here, the authentication is carried out with the security factors, namely location profile, one-time password, spatial information, session password, a hashing function, and so on. Initially, the user and the server are registered in the authentication process, and then, hashing functions and AES are used to perform multi-level authorization and authentication processes. Thus, the proposed scheme improves the security of the P2P network. Using the proposed system, the hit ratio obtained is 0.9, and the success rate is 0.7666.

Opportunistic forwarding mechanism in delay tolerant networks (DTN) makes the network exposed to vulnerabilities. Providing security to existing routing protocols available for delay tolerant network becomes very difficult due to unavailability of sufficient contacts. It is necessary to design a secure routing protocol to overcome these issues. Energy is one of the crucial parameters in data forwarding and incentives should be offered to vehicular DTN nodes on the basis of energy spent for a particular message. This paper presents the secure routing mechanism which is based on the trust value of the vehicular DTN nodes. Incentive scheme is based on energy spent by the vehicular DTN node for forwarding data successfully. Routing is based on the trust value of the vehicular DTN nodes and incentive will be offered on successful delivery of the message. A source node offers the payment for successful delivery based on the time in which the message is delivered. The trust authority evaluates the credit and trust value for the participating vehicular DTN nodes based on energy and efforts put in successful delivery of the message.

This paper presents a random forest algorithm to detect confusion affective states in virtual learning systems. The learning contents and examination questions are based on Bloom’s taxonomy cognitive levels. The proposed methodology captures learner’s behavioral interaction features. The confusion detection accuracy is above 90%.

This paper has proposed an affective learning system to detect the affective state of learner by using random forest algorithm. The proposed system analyzes various hyper parameters of the algorithm for achieving best performance in terms of accuracy and Cohen's Kappa for affective learning dataset.

Cardiovascular diseases (CVD) are the major cause of mortality globally, as well as in India. Most of the deaths caused by CVD are sudden and without giving any chance to provide any medical help. To avoid such impulsive accidental deaths precautions are always required. Due to this heart patients require continuous monitoring of certain vital body parameters such as heart rate, pulse rate and electrocardiogram (ECG) showing current health status clearly. In this paper we are presenting 3 - tier architecture of our prototype healthcare monitoring system using wireless sensor network (WSN) which is developed to continuously monitor certain body parameters of patient. Different biosensors available to measure heart rate, body oxygen level and temperature are attached to Arduino Nano board and recorded signals are sent to server using Node MCU ESP8266 wireless communication. Data is made available on remote servers for doctors and caregivers using ThingSpeak, an internet of things (IOT) application. In case of emergency caregivers can be notified using smart phone alerts. The system is useful for cardiac patients and can be used for infant or baby care and elderly care in home and hospitals. Accuracy of the system is found 95% with the response time of 10 seconds.

The paper presents methodology for mapping of learner interaction patterns in virtual learning system to the affective state. A learning activity can lead the learner to confused or confident state of mind. This affective state of learner can be identified by interaction pattern analysis. The examination mode of learning system is designed with questionnaire based on Bloom's taxonomy cognitive levels. We present an approach for establishing relationship between cognitive level test performance of learner and affective state. Various non-intrusive interaction parameters captured during learning activity act as input features. We find that random forest algorithm provides very good accuracy in determining affective state.

This paper presents a solution for priority-based data transmission in heterogeneous wireless sensor networks. Considering the requirements of each event separately while delivering a data simultaneously is a challenging task in the sensor networks. Therefore, we present the PriTLP protocol for prioritizing the information at various data processing units in the multi-hop topology network. It brings a distributed approach for taking decisions on behalf of the sink node which fastens the data processing, reduces the communication delays, and prolongs the network life. It performs two operations, namely data prioritization and scheduling; and identifying the congestion degree of the network. The reported work is implemented and validated over the RF TestBed by managing the buffer level. It shows high packet delivery ratio, greater throughput, and fewer communication delays of high priority-based traffic flow over regular flows.

In the world, roughly more than 3 million people are affected by muscle power loss diseases which cause lack of communication. Further, this lack of communication is a severe problem with hunger and stress, which sometimes proves to be fatal. It is essential to monitor physical parameters such as hunger and mental stress of the patient. To observe hunger and stress, galvanic skin response (GSR) sensor is a most preferred method because it measures the conductance of skin due to sweating. We have designed new hunger and stress monitoring system (HS-MS) that helps patients and their caretakers to monitor stress and hunger level. HS-MS is two electrodes system that attaches to two fingers (index and middle) of the patient and monitors starvation and tension. According to the response of the sensor, caretakers can identify hunger and even the mental stress conditions of the patient. In all, 35 patients were examined using HS-MS system and 20 of them were used as a control. Overall system accuracy was found out to be 86.6% and response time of HS-MS 5 seconds. Sensitivity with respect to hunger and stress was about 99.9% and 73.3% respectively. Thus HS-MS can be identified as a helpful tool to provide comfort to the patient easily and can be used in hospitals or homes with lonely elderly people.

Wireless Sensor Network (WSN) can be effectively used for continuous monitoring of patient in hospitals and in homes for elderly and baby care. Proposed system is a smart healthcare monitoring system using WSN which can monitor patients admitted in the hospital continuously without any interference of wires around patient bed. We are accentuating the advantage of wireless sensor network over wired system by attaching various advanced sensors to this network to collect various body parameters of a patient such as blood pressure, temperature, heart rate, pulse rate and blood oxygen level (SPO2) wirelessly. A kind of WSN called as WBAN is used for this purpose. Many designing requirements like flexibility, miniaturization, portability, non-intrusiveness, and low cost are studied and considered to the make system more efficient. Different available wireless standards are compared for the intermediate communication based on various parameters. Proposed system is a Healthcare Monitoring System with ESP8266 NodeMcu WiFi wireless communication using Arduino Nano boards. This system can detect the abnormal health conditions of patients, issue an alarm in emergency conditions and send SMS/E-mail to the physician, caregiver and relatives of patient.

Deduplication is maturing as a standard attribute on backup and archives, whereby the aim is to free the storage space by removing the duplicates. Considering the storage room demand and justifiable deletion, this paper proposes a multi-container intelligent deduplication image archive system; where analogous images are disposed from the system based on the similarity approach. Similarity-aware image deduplication is achieved by calculating image fingerprints and the images are deleted when their hamming distance matches the predefined threshold. A probability model is addressed for the overall probability of getting similar images on the respective containers based on their relative storage and similarity scores of the images. In addition, the linear optimisation model is formulated to target data minimisation and storage space maximisation; which is further verified with the dataset. We perform experimentation of our work on the existing as well as synthesised datasets and various accuracy metrics are calculated in terms of precision, recall, f-score and deduplication ratio. It is observed that binary hashes used in our system give the fair contribution in removing similar images.

This paper intends to perform de-duplication for enhancing the storage optimization by utilizing the similarity in mutual information. Hence, this paper contributes by proposing a hybrid fingerprint extracting using SH and HC algorithms. Secondly, the data is clustered using the latest technique called as SOMI-GO to extract the metadata. The extracted metadata is stored in metadata server which provides better storage optimization and de-duplication. SOMI-GO is adopted as it provides maximum second-order mutual information based on the similarity index. The proposed SOMI-GO technique is compared with the existing methods such as K-means, K-mode, ED-PSO, ED-GA and ED-GWO in terms of accuracy, TPR, TNR and performance time and the significance of the SOMI-GO method is described.

Many gazettes, toys, sensors, instruments, etc., devices are mushrooming in the electronics market these days which are running with different operating systems and application frameworks. In Mobile phones also many platforms are available with its own stack, right from hardware level to application level. So it is difficult to all the mobile phones or devices with same characteristics, performance, and features. The conclusive success of a platform entirely depends on its security to the user data ultimately, it constructs the global market. We present here a comparative study of four Mobile Operating Systems architecture and security perspectives of each. Moreover, experiments are carried out with Windows and android smartphone to study the cryptographic performance in these devices which plays as decisive parameters for future applications and system developers to implement secured devices and applications. We show that although algorithms characteristics are fixed, due to different architectures and dependencies in different devices with different operating systems, same efficiency, and performance is not guaranteed by cryptographic as well as other data structure algorithms.

Location based service is an integral part of day to day life. Many location recommendation algorithms are proposed in the past. This paper investigates various approaches currently available for implementing location recommendation systems.

There are several approaches to reduce the energy consumption. Among them, one approach which allows for reducing the transmission energy consumption is Delay Tolerant Networks (DTNs). Several techniques are adopted to optimize the energy efficiency. Adjusting the resource allocation and decreasing the equipment usages are the basic two categories, which are used to reduce the energy consumption. With the increasing data transmission rate the energy consumption increases, which result in the diminishing of its efficiency. So, it is a necessity to manage the trade-off between energy and performance in Delay Tolerant Networks. The DTN nodes commonly operate on low-power battery resource; hence, there is need of improving the energy efficiency by using appropriate technique to increase the lifetime of the node and also to increase the probability of delivering the bundle. For that purpose, this paper describes the various techniques to achieve energy efficiency in Delay Tolerant Networks.

Healthcare applications based on WSN are gaining high popularity all over the world due to their features like flexibility, mobility and ease of constant monitoring of the patient. The main focus of such system is remote monitoring of patient, inside and outside the hospital room and in ICU.

As the feature of delay tolerant networks (DTNs) is open, and intermittent, any node can participate in this type of network. Trusting a DTN node becomes a critical task for the routing algorithms. For the past few years, security techniques have evolved and a lot of research has been carried out in this area. Among these security techniques, trust-based, reputation-based systems, and incentive-based security schemes are discussed in this paper. These techniques are useful to detect selfish DTN nodes and noncooperative DTN nodes. These schemes for DTN nodes are the most common methods to detect malicious, selfish DTN nodes.

Increase in digital data demands a smart storage technique which provides quick storage and faster recovery of the stored data. This voluminous data needs an intelligent data science tools and methods to struggle for the space required for efficiently storing the data. Deduplication is one the emerging and widely used techniques these days for reducing the data size and then transferring it over the network thus reducing the network bandwidth. Main aim of Deduplication is to reduce storage space by allowing only unique data. In this paper, we present the review of existing Deduplication solutions and propose enhanced cache mechanism approach for efficient Deduplication over distributed system.

Wireless sensor network (WSNs) has potential to solve the problem automatically with less or no human intervention in most of the cases. Time constraint event (TCE) and non-time constraint (NTCE) event are two broad categories in heterogeneous WSNs. To address the QoS parameters in TCE and nTCE type of applications are crucial job in resource constraint multi-event WSNs. The queue scheduler performs those set of actions which are necessary to achieve the desired QoS parameters for each distinct event separately in a sensor network. A study mainly focuses on priority-based reliability with considering their different levels of priority of traffic. Decisions are taken at various intermediate nodes by managing queue. For each level of priority a separate queue is maintained. Queue management is the heart of proposed priority architecture for achieving quality of services. Due to proper queuing operation, scheduler takes the right decision at right time to attain the required reliability. Scheduler accomplishes desired goals of every application by handling their priority and deadlines.

The traditional storage approaches are being challenged by huge data volumes. In multimedia content, every file does not necessarily get tagged as an exact duplicate; rather they are prone to editing and resulting in similar copies of the same file. This paper proposes the similarity-based deduplication approach to evict similar duplicates from the archive storage, which compares the samples of binary hashes to identify the duplicates. This eviction is done by initially dividing the query video into dynamic key frames based on the video length. Binary hash codes of these frames are then compared with existing key frames to identify the differences. The similarity score is determined based on these differences, which decides the eradication strategy of duplicate copy. Duplicate elimination goes through two levels, namely removal of exact duplicates and similar duplicates. The proposed approach has shortened the comparison window by comparing only the candidate hash codes based on the dynamic key frames and aims the accurate lossless duplicate removals. The presented work is executed and tested on the produced synthetic video dataset. Results show the reduction in redundant data and increase in the storage space. Binary hashes and similarity scores contributed to achieving good deduplication ratio and overall performance.

The heterogeneous wireless sensor network is currently finding the ways to handle the various issues of storage, communication, and computation. Due to limited resources available at sensor nodes, protocols need to be carefully designed to solve the current problems. While designing the prioritized transport layer protocol for multi-event, the several design issues are required to take into consideration cautiously. Therefore, this paper discusses the various issues of the prioritized transport protocol for heterogeneous wireless sensor networks like variable reliability, loss recovery, handling multi-events, congestion control, fairness, energy consumption, query response time, and many more in order to make efficient priority based transport protocol especially for heterogeneous wireless sensor network. The precedence control scheme achieves some improvements in throughput, packet delivery ratio as compared to non precedence control scheme.

Increase in enormous amount of digital data needs more storage space, which in turn significantly increases the cost of backup and its performance. Traditional backup solutions do not provide any inherent capability to prevent duplicate data from being backed up. Backup of duplicate data significantly increases the backup time and unnecessary consumption of resources. Data Deduplication plays an important role in eliminating this redundant data and reducing the storage consumption. Its main intend is how to reduce more duplicates efficiently, removing them at high speed and to achieve good duplicate removal ratio. Many mechanisms have been proposed to meet these objectives. It has been observed that achieving one objective may affect the other. In this paper we classify and review the existing deduplication techniques. We also present evaluation of deduplication algorithms by measuring their performance in terms of complexity and efficiency with unstructured files. We propose an efficient means to achieve high deduplication ratio with minimum backup window. We also indicate some key issues need to focus in the future work.