A reliable cross layer routing scheme (CL-RS) for wireless sensor networks to prolong network lifetime

Design of conventional protocols for wireless sensor networks(WSN) are mainly based on energy management. The solutions for layered protocol of the WSN network are inefficient as sensors network mainly delivers real-time content thus, cross layer communication between layers of the protocol stack is highly required. In this paper, a reliable cross layer routing scheme (CL - RS) is proposed to balance energy to achieve prolonged lifetime through controlled utilization of limited energy. CL - RS considers 2 adjacent layers namely, MAC layer and network layer. Optimization issues are identified in these two layers and solutions are provided to reduce energy consumption thereby increasing network lifetime. To achieve higher energy efficiency MAC layer protocols compromise on packet latency. It is essential to attempt reduce the end-to-end delay and energy consumption using low duty cycle cross layer MAC (CL-MAC). The joint optimization design is formulated as a linear programming problem. The network is partitioned into four request zones to enable increase in network performance by using an appropriate duty cycle and routing scheme. We demonstrate by simulations that the strategy designed by combining (CL - RS) and (CL-MAC) algorithms at each layer significantly increases the network lifetime and a relation exists between the network lifetime maximization and the reliability constraint. We evaluate the performance of the proposed scheme under different scenarios using ns-2. Experimental results shows that proposed scheme outperforms the layered AODV in terms of packet loss ratio, end-to-end delay, control overhead and energy consumption

A Grid-Enabled Infrastructure for Resource Sharing, E-Learning, Searching and Distributed Repository Among Universities

In the recent years, service-based approaches for sharing of data among repositories and online learning are rising to prominence because of their potential to meet the requirements in the area of high performance computing. Developing education based grid services and assuring high availability reliability and scalability are demanding in web service architectures. On the other hand, grid computing provides flexibility towards aggregating distributed CPU, memory, storage, data and supports large number of distributed resource sharing to provide the full potential for education like applications to share the knowledge that can be attainable on any single system. However, the literature shows that the potential of grid resources for educational purposes is not being utilized yet. In this paper, an education based grid framework architecture that provides promising platform to support sharing of geographically dispersed learning content among universities is developed. It allows students, faculty and researchers to share and gain knowledge in their area of interest by using e-learning, searching and distributed repository services among universities from anywhere, anytime. Globus toolkit 5.2.5 (GTK) software is used as grid middleware that provides resource access, discovery and management, data movement, security, and so forth. Furthermore, this work uses the OGSA-DAI that provides database access and operations. The resulting infrastructure enables users to discover education services and interact with them using the grid portal

A pre-emptive multiple queue based congestion control for different traffic classes in WSN

Traffic in wireless sensor networks (WSN) exhibits a many-to-one pattern in which multiple source nodes send sensing data to a single sink node. Since bandwidth, processor and memory are highly constrained in WSN, packet loss is common when a great deal of traffic rushes to sink. The system must provide differentiated service to individual traffic classes. In this paper, a pre-emptive multiple queue based congestion control mechanism is proposed. To detect congestion and to provide QoS for high priority traffic multiple buffers are used. Using this mechanism, high system utilization, reduced packet waiting time, and reduced packet drop probability are achieved. An analytical model is developed to predict the performance of the proposed mechanism by calculating the performance measures including system throughput, drop probability of packets, and mean queue length. By comparing analytical and simulation results the effectiveness and accuracy of the model is demonstrated. Markovian process is used to develop the analytical model and ns-2 for evaluating the performance of the mechanism

Hybrid spot instance based resource provisioning strategy in dynamic cloud environment

Utilization of resources to the maximum extent in large scale distributed cloud environment is a major challenge due to the nature of cloud. Spot Instances in the Amazon Elastic Compute Cloud (EC2) are provisioned based on highest bid with no guarantee of task completion but incurs the overhead of longer task execution time and price. The paper demonstrates the last partial hour and cost overhead that can be avoided by the proposed strategy of Hybrid Spot Instance. It aims to provide reliable service to the ongoing task so as to complete the execution without abruptly interrupting the long running tasks by redefining the bid price. The strategy also considers that on-demand resource services can be acquired when spot price crosses on-demand price and thereby availing high reliability. This will overcome the overhead involved during checkpointing, restarting and workload migration as in the existing system, leading to efficient resources usage for both the providers and users. Service providers revenue is carefully optimized by eliminating the free issue of last partial hour which is a taxing factor for the provider. Simulation carried out based on real time price of various instances considering heterogenous applications shows that the number of out-of-bid scenarios can be reduced largely which leads to the increased number of task completion. Checkpointing is also minimized maximally due to which the overhead associated with it is reduced. This resource provisioning strategy aims to provide preference to existing customers and the task which are nearing the execution completion

Optimized congestion aware energy efficient traffic load balancing scheme for routing in wireless sensor networks

Load imbalance among hot spot nodes causes network congestion and earliest energy depletion of nodes in wireless sensor networks. This increases the probability of disconnecting or partitioning the network and premature death of entire network. The inefficiency in the WSN is more attributed to load imbalance or unbiased traffic. In this paper, an optimized congestion aware (OCAEE-LB) energy efficient traffic load balancing scheme for routing in WSN is proposed. The scheme utilizes the neglected information during route discovery process and considers a composite routing metric to determine congested status of a node and to enforce the traffic load balancing. The proposed scheme is simulated using ns-2 and the results demonstrate that the proposed mechanism performs better than the existing AODV-LB algorithm of various performance metrics such as, packet delivery ratio, throughput, routing overhead, end-to-end delay, load distribution and energy consumption

Cost and fault-tolerant aware resource management for scientific workflows using hybrid instances on clouds

Cloud service providers are offering computing resources at a reasonable price as a pay-per-use model. Further, cloud service providers have also introduced different pricing models like spot, blockspot and spotfleet instances that are cost effective and user’s have to go through the bidding to balance the reliability and monetary costs. Henceforth, Scientific Workflows (SWf) that are used to model applications of high throughput, computation and complex large-scale data analysis are significantly adopting these computing resources. Nevertheless, spot instances are terminated when the market spot price exceeds the users bid price. Moreover, failures are inevitable in such a large distributed systems and often pose a challenge to design a fault-tolerant scheduling algorithm for SWf. This paper presents an efficient, low-cost and fault-tolerant scheduling algorithm and a bidding strategy to minimize the

A Single-Tube, Functional Marker-Based Multiplex PCR Assay for Simultaneous Detection of Major Bacterial Blight Resistance Genes Xa21, xa13 and xa5 in Rice

AbstractIn marker-assisted breeding for bacterial blight (BB) resistance in rice, three major resistance genes, viz., Xa21, xa13 and xa5, are routinely deployed either singly or in combinations. As efficient and functional markers are yet to be developed for xa13 and xa5, we have developed simple PCR-based functional markers for both the genes. For xa13, we designed a functional PCR-based marker, xa13-prom targeting the InDel polymorphism in the promoter of candidate gene Os8N3 located on chromosome 8 of rice. With respect to xa5, a multiplex-PCR based functional marker system, named xa5FM, consisting of two sets of primer pairs targeting the 2-bp functional nucleotide polymorphism in the exon II of the gene TFIIAɤ5 (candidate for xa5), has been developed. Both xa13-prom and xa5FM can differentiate the resistant and susceptible alleles for xa13 and xa5, respectively, in a co-dominant fashion. Using these two functional markers along with the already reported functional PCR-based marker for Xa21 (pTA248), we designed a single-tube multiplex PCR based assay for simultaneous detection of all the three major resistance genes and demonstrated the utility of the multiplex marker system in a segregating population

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

MQTT and blockchain sharding: An approach to user-controlled data access with improved security and efficiency

The rapid growth of the Internet of Things (IoT) has raised security concerns, including MQTT protocol-based applications that lack built-in security features and rely on resource-intensive Transport Layer Security (TLS) protocols. This paper presents an approach that utilizes blockchain technology to enhance the security of MQTT communication while maintaining efficiency. This approach involves using blockchain sharding, which enables higher scalability, improved performance, and reduced computational overhead compared to traditional blockchain approaches, making it well-suited for resource-constrained IoT environments. This approach leverages Ethereum blockchain's smart contract mechanism to ensure trust, accountability, and user privacy. Specifically, we introduce a shard-based consensus mechanism that enables improved security while minimizing computational overhead. We also provide a user-controlled and secured algorithm using Proof-of-Access implementation to decentralize user access control to data stored in the blockchain network. The proposed approach is analyzed for usability, including metrics such as bandwidth consumption, CPU usage, memory usage, delay, access time, storage time, and jitter, which are essential for IoT application requirements. The analysis demonstrated that the approach reduces resource consumption, and the proposed system outperforms TLS and existing blockchain approaches in these metrics, regardless of the choice of the MQTT broker. Additionally, thoroughly addressing future research directions, including issues and challenges, ensures careful consideration of potential advancements in this domain