Efficient reliable broadcast for commodity clusters

High-speed collective communication is the key to achieve high-performance computing in parallel computing. In the past, collective operations are usually implemented using unicast operations. We proposed a new architecture EQA (Enhanced Queue Architecture) for implementing high-speed collective operations in a cluster. With the incorporation of EQA and the hardware broadcast facility in network switches, an efficient reliable broadcast operation is implemented in a DP-SMP communication subsystem. With EQA, the computation, memory and network resources can be utilized efficiently. We evaluated the performance of the broadcast operation in a commodity cluster with fast Ethernet connection. We found that the hardware-based broadcast from DP-SMP with EQA outperforms the software-based broadcast operation. The use of EQA in broadcast operation could reduce the memory consumption by almost 40%. DP-SMP with EQA has proven to be an efficient communication mechanism for coupling commodity clusters.published_or_final_versio

Toward Third Generation Internet Desktop Grids

Projects like SETI@home and Folding@home have popularized Internet Desktop Grid (IDG) computing. The first generation of IDG projects scalled to millions of participatings but was dedicated to a specific application. BOINC, United Device and XtremWeb belong to a second generation of IDG platforms. Their architecture was designed to accommodate many applications but has drawbacks like limited security and a centralized architecture. In this paper we present a new design for Internet Desktop Grid, following a layered approach. The new architecture establishes an overlay network, giving the participating nodes direct communication capabilities. From that basis many key mechanisms of IDG can be implemented using existing cluster tools and extra IDG specificic software. As a proof of concept, we run a bioinformatic application on a third generation IDG, based on a connectivity service (PVC), an existing job scheduler (Condor), a high performance data transport service (Bittorent) and a custom result certification mechanism

Computing in the RAIN: a reliable array of independent nodes

The RAIN project is a research collaboration between Caltech and NASA-JPL on distributed computing and data-storage systems for future spaceborne missions. The goal of the project is to identify and develop key building blocks for reliable distributed systems built with inexpensive off-the-shelf components. The RAIN platform consists of a heterogeneous cluster of computing and/or storage nodes connected via multiple interfaces to networks configured in fault-tolerant topologies. The RAIN software components run in conjunction with operating system services and standard network protocols. Through software-implemented fault tolerance, the system tolerates multiple node, link, and switch failures, with no single point of failure. The RAIN-technology has been transferred to Rainfinity, a start-up company focusing on creating clustered solutions for improving the performance and availability of Internet data centers. In this paper, we describe the following contributions: 1) fault-tolerant interconnect topologies and communication protocols providing consistent error reporting of link failures, 2) fault management techniques based on group membership, and 3) data storage schemes based on computationally efficient error-control codes. We present several proof-of-concept applications: a highly-available video server, a highly-available Web server, and a distributed checkpointing system. Also, we describe a commercial product, Rainwall, built with the RAIN technology

A Resource Intensive Traffic-Aware Scheme for Cluster-based Energy Conservation in Wireless Devices

Wireless traffic that is destined for a certain device in a network, can be exploited in order to minimize the availability and delay trade-offs, and mitigate the Energy consumption. The Energy Conservation (EC) mechanism can be node-centric by considering the traversed nodal traffic in order to prolong the network lifetime. This work describes a quantitative traffic-based approach where a clustered Sleep-Proxy mechanism takes place in order to enable each node to sleep according to the time duration of the active traffic that each node expects and experiences. Sleep-proxies within the clusters are created according to pairwise active-time comparison, where each node expects during the active periods, a requested traffic. For resource availability and recovery purposes, the caching mechanism takes place in case where the node for which the traffic is destined is not available. The proposed scheme uses Role-based nodes which are assigned to manipulate the traffic in a cluster, through the time-oriented backward difference traffic evaluation scheme. Simulation study is carried out for the proposed backward estimation scheme and the effectiveness of the end-to-end EC mechanism taking into account a number of metrics and measures for the effects while incrementing the sleep time duration under the proposed framework. Comparative simulation results show that the proposed scheme could be applied to infrastructure-less systems, providing energy-efficient resource exchange with significant minimization in the power consumption of each device.Comment: 6 pages, 8 figures, To appear in the proceedings of IEEE 14th International Conference on High Performance Computing and Communications (HPCC-2012) of the Third International Workshop on Wireless Networks and Multimedia (WNM-2012), 25-27 June 2012, Liverpool, U

Secure and Privacy-Preserving Data Aggregation Protocols for Wireless Sensor Networks

This chapter discusses the need of security and privacy protection mechanisms in aggregation protocols used in wireless sensor networks (WSN). It presents a comprehensive state of the art discussion on the various privacy protection mechanisms used in WSNs and particularly focuses on the CPDA protocols proposed by He et al. (INFOCOM 2007). It identifies a security vulnerability in the CPDA protocol and proposes a mechanism to plug that vulnerability. To demonstrate the need of security in aggregation process, the chapter further presents various threats in WSN aggregation mechanisms. A large number of existing protocols for secure aggregation in WSN are discussed briefly and a protocol is proposed for secure aggregation which can detect false data injected by malicious nodes in a WSN. The performance of the protocol is also presented. The chapter concludes while highlighting some future directions of research in secure data aggregation in WSNs.Comment: 32 pages, 7 figures, 3 table

MODLEACH: A Variant of LEACH for WSNs

Wireless sensor networks are appearing as an emerging need for mankind. Though, Such networks are still in research phase however, they have high potential to be applied in almost every field of life. Lots of research is done and a lot more is awaiting to be standardized. In this work, cluster based routing in wireless sensor networks is studied precisely. Further, we modify one of the most prominent wireless sensor network's routing protocol "LEACH" as modified LEACH (MODLEACH) by introducing \emph{efficient cluster head replacement scheme} and \emph{dual transmitting power levels}. Our modified LEACH, in comparison with LEACH out performs it using metrics of cluster head formation, through put and network life. Afterwards, hard and soft thresholds are implemented on modified LEACH (MODLEACH) that boast the performance even more. Finally a brief performance analysis of LEACH, Modified LEACH (MODLEACH), MODLEACH with hard threshold (MODLEACHHT) and MODLEACH with soft threshold (MODLEACHST) is undertaken considering metrics of throughput, network life and cluster head replacements.Comment: IEEE 8th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA'13), Compiegne, Franc

Smart handoff technique for internet of vehicles communication using dynamic edge-backup node

© 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/electronics9030524A vehicular adhoc network (VANET) recently emerged in the the Internet of Vehicles (IoV); it involves the computational processing of moving vehicles. Nowadays, IoV has turned into an interesting field of research as vehicles can be equipped with processors, sensors, and communication devices. IoV gives rise to handoff, which involves changing the connection points during the online communication session. This presents a major challenge for which many standardized solutions are recommended. Although there are various proposed techniques and methods to support seamless handover procedure in IoV, there are still some open research issues, such as unavoidable packet loss rate and latency. On the other hand, the emerged concept of edge mobile computing has gained crucial attention by researchers that could help in reducing computational complexities and decreasing communication delay. Hence, this paper specifically studies the handoff challenges in cluster based handoff using new concept of dynamic edge-backup node. The outcomes are evaluated and contrasted with the network mobility method, our proposed technique, and other cluster-based technologies. The results show that coherence in communication during the handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.Published onlin

Predictive intelligence to the edge through approximate collaborative context reasoning

We focus on Internet of Things (IoT) environments where a network of sensing and computing devices are responsible to locally process contextual data, reason and collaboratively infer the appearance of a specific phenomenon (event). Pushing processing and knowledge inference to the edge of the IoT network allows the complexity of the event reasoning process to be distributed into many manageable pieces and to be physically located at the source of the contextual information. This enables a huge amount of rich data streams to be processed in real time that would be prohibitively complex and costly to deliver on a traditional centralized Cloud system. We propose a lightweight, energy-efficient, distributed, adaptive, multiple-context perspective event reasoning model under uncertainty on each IoT device (sensor/actuator). Each device senses and processes context data and infers events based on different local context perspectives: (i) expert knowledge on event representation, (ii) outliers inference, and (iii) deviation from locally predicted context. Such novel approximate reasoning paradigm is achieved through a contextualized, collaborative belief-driven clustering process, where clusters of devices are formed according to their belief on the presence of events. Our distributed and federated intelligence model efficiently identifies any localized abnormality on the contextual data in light of event reasoning through aggregating local degrees of belief, updates, and adjusts its knowledge to contextual data outliers and novelty detection. We provide comprehensive experimental and comparison assessment of our model over real contextual data with other localized and centralized event detection models and show the benefits stemmed from its adoption by achieving up to three orders of magnitude less energy consumption and high quality of inference