PFPS: Priority-First Packet Scheduler for IEEE 802.15.4 Heterogeneous Wireless Sensor Networks

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

A Deterministic Eviction Model for Removing Redundancies in Video Corpus

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

A Review of Image Super Resolution using Deep Learning

The image processing methods collectively known as super-resolution have proven useful in creating high-quality images from a group of low-resolution photographic images. Single image super resolution (SISR) has been applied in a variety of fields. The paper offers an in-depth analysis of a few current picture super resolution works created in various domains. In order to comprehend the most current developments in the development of Image super resolution systems, these recent publications have been examined with particular emphasis paid to the domain for which these systems have been designed, image enhancement used or not, among other factors. To improve the accuracy of the image super resolution, a different deep learning techniques might be explored. In fact, greater research into the image super resolution in medical imaging is possible to improve the data's suitability for future analysis. In light of this, it can be said that there is a lot of scope for research in the field of medical imaging

Use of Key Points and Transfer Learning Techniques in Recognition of Handedness Indian Sign Language

The most expressive way of communication for individuals who have trouble speaking or hearing is sign language. Normal people are unable to comprehend sign language. As a result, communication barriers are put up. Majority of people are right-handed. Statistics say that, an average population of left-handed person in the world is about 10%, where they use left hand as their dominating hand. In case of hand written text recognition, if the text is written by left-handed or right-handed person, then there would not be any problem in recognition neither for human and nor for computer. But same thing is not true for sign language and its detection using computer. When the detection is performed using computer vision and if it falls into the category of detection by appearance, then it might not detect correctly. In machine and deep learning, if the model is trained using just one dominating hand, let’s say right hand, then the predictions can go wrong if same sign is performed by left-handed person. This paper addresses this issue. It takes into account the signs performed by any type of signer: left-handed, right-handed or ambidexter. In proposed work is on Indian Sign Language (ISL). Two models are trained: Model I, is trained on one dominating hand and Model II, is trained on both the hands. Model II gives correct predictions regardless of any type of signer. It recognizes alphabets and numbers in ISL. We used the concept of Key points and Transfer Learning techniques for implementation. Using this approach, models get trained quickly and we could achieve validation accuracy of 99%

VSRS: Variable Service Rate Scheduler for Low Rate Wireless Sensor Networks

This paper proposes a variable service rate scheduler VSRS for heterogeneous wireless sensor and actuator networks (WSANs). Due to recent advancement, various applications are being upgraded using sensor networks. Generally, traffic consists of delay sensitive and delay tolerant applications. Handling such traffic simultaneously is a critical challenge in IEEE 802.15.4 sensor network. However, the standard CSMA/CA does not focus on traffic-based data delivery. Therefore, this paper presents a solution for prioritybased traffic over no-priority i.e. regular traffic using CSMA/CA IEEE 802.15.4 MAC sublayer. The VSRS scheduler uses a queuing model for scheduling incoming traffic at an actor node using a dual queue. The scheduler updates priority of each incoming packet dynamically using network priority weight metric. The VSRS scheduler scans queues and picks the highest network priority packet. A packet weight is updated after selection from the respective queue. This core operation of an actor node offers good packet delivery ratio, throughput, and less delay experience of long distance traveled packets against no priority traffic. The work is validated using theoretical analysis and computer generated network simulators; proves that the priority based approach using weight factor works better over the First-Come-First-Serve (FCFS) mechanism

A Data Transmission Protocol for Wireless Sensor Networks: A Priority Approach

Recent development in the field of a wireless sensor network has shown the significant improvement and has emerged as a new energy efficient wireless technology for low data rate applications. Handling different types of event data altogether is a crucial task in the sensor networks. This paper presents the solution to the problem of heterogeneous data transmission of long distance prioritised nodes in low data rate wireless sensor networks (LR-WSNs). The solution comprises three main algorithms, namely data reporting, traffic scheduling, and centralised reporting rate mechanism. The data reporting algorithm reports the demanded data in each specified decision window size with variable reporting rate. The traffic aware packet scheduling algorithm performs the packet reprioritisation and scheduling. The priority assignment is designed based on the data priority and hop count. It serves transient traffic against newly sensed packets, or less hop distance travelled packets. As a result, it minimises the chances of dying earlier than its deadline. The third algorithm presents the flexible data gathering approach based on the level of the buffer either sensed by its own or recently received information from hop node. It uses a decision interval window for managing the frequency of data delivery. This centralised decision approach makes the sink node more adaptive for data gathering and controlling the active source nodes. This multi-tier framework functions over CSMA/CA due to its unique feature of energy saving, especially for LR-WSNs. The reported work is simulated and examined over various scenarios in the multi-hop wireless sensor networks. Moreover, the performance of the scheduler proves better data transmission rate for prioritybased traffic over regular traffic flows; approximately 7% over First-Come-First-Served (FCFS) and 5% against Precedence Control Scheme (PCS) mechanism using theoretical analysis and computer simulations

Privacy Aware Monitoring of Mobile Users in Sensor Networks Environment

Abstract—Due to complex monitoring systems in various business domains, secrecy and privacy has become critical issue for movable resources including human being. In a mobile object monitoring systems, balancing computing resources and quality of privacy is required.  Objects can be mobile devices or users or any other moving entity. This work is presented in wireless sensor network environment. Earlier work does not consider presence of mobile objects in 3D space. We can observe that objects also carry Z axis in city area where high rise buildings are present.  Earlier monitoring applications are mainly designed in two dimensional space to protect privacy. Our novelty is to suggest and design mechanism that reflect Z position (height) of mobile objects for protecting privacy. While calculating cloaking area and counting of objects, height is also considered as third dimension. This results in better location privacy as compared to the privacy delivered by the scheme that considers two dimensional space. We have presented performance, communications cost and privacy strength of modified 3D quality algorithm and 3D resource algorithm. Moreover, we present novel containment resolution algorithm that handles duplicate counting due to 3D presence of wireless system and mobile devices.</p

PriTLP: A Priority-based Transport Layer Protocol for Low Rate Wireless Sensor Networks

Abstract 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