A Framework for Secure and Survivable Wireless Sensor Networks

Wireless sensor networks increasingly become viable solutions to many challenging problems and will successively be deployed in many areas in the future. A wireless sensor network (WSN) is vulnerable to security attacks due to the insecure communication channels, limited computational and communication capabilities and unattended nature of sensor node devices, limited energy resources and memory. Security and survivability of these systems are receiving increasing attention, particularly critical infrastructure protection. So we need to design a framework that provide both security and survivability for WSNs. To meet this goals, we propose a framework for secure and survivable WSNs and we present a key management scheme as a case study to prevent the sensor networks being compromised by an adversary. This paper also considers survivability strategies for the sensor network against a variety of threats that can lead to the failure of the base station, which represents a central point of failure.key management scheme, security, survivability, WSN

Developing Word-aligned Myanmar-English Parallel Corpus based on the IBM Models

Word alignment in bilingual corpora has been an active research topic in the Machine Translation research groups. Corpus is the body of text collections, which are useful for Language Processing (NLP). Parallel text alignment is the identification of the corresponding sentences in the parallel text. Large collections of parallel level are prerequisite for many areas of linguistic research. Parallel corpus helps in making statistical bilingual dictionary, in supporting statistical machine translation and in supporting as training data for word sense disambiguation and translation disambiguation. Nowadays, the world is a global network and everybody will be learned more than one language. So, multilingual corpora are more processing. Thus, the main purpose of this system is to construct word-aligned parallel corpus to be able in Myanmar-English machine translation. One useful concept is to identify correspondences between words in one language and in other language. The proposed approach is based on the first three IBM models and EM algorithm. It also shows that the approach can also be improved by using a list of cognates and morphological analysis

Distributed Energy Efficient Cluster Formation for Wireless Sensor Networks

In large scale wireless sensor networksclustering is often used for improving energyefficiency and achieving scalable performance. In theclustered environment, data gathered by the nodes istransmitted to the base station through cluster-heads(CHs). As the nodes will communicate data overshorter distances in such an environment, the energyspent in the network is likely to be substantiallylower compared to when every sensor communicatesdirectly to the base station. The essential operationin sensor node clustering is to select a set of clusterheadsfrom the set of nodes in the network, and thencluster the remaining nodes with these heads. In thispaper, we propose a distributed energy efficientcluster formation (DEECF) algorithm for wirelesssensor networks. The cluster-head selectionalgorithm of DEECF is extended the LEACH’sstochastic cluster-head selection algorithm byconsidering the additional parameters, the residualenergy of the node relative to the residual energy ofthe network. We also compare our DEECF withLEACH in terms of network lifetime. The simulationresults demonstrate that DEECF can achieve highenergy efficiency and prolong network lifetime

A Framework for Secure and Survivable Wireless Sensor Networks

Wireless sensor networks increasingly become viable solutions tomany challenging problems and will successively be deployed in many areas inthe future. A wireless sensor network (WSN) is vulnerable to security attacksdue to the insecure communication channels, limited computational andcommunication capabilities and unattended nature of sensor node devices,limited energy resources and memory. Security and survivability of thesesystems are receiving increasing attention, particularly critical infrastructureprotection. So we need to design a framework that provide both security andsurvivability for WSNs. To meet this goals, we propose a framework for secureand survivable WSNs and we present a key management scheme as a case studyto prevent the sensor networks being compromised by an adversary. This paperalso considers survivability strategies for the sensor network against a variety ofthreats that can lead to the failure of the base station, which represents a centralpoint of failure

CPU Usage Prediction Models for Virtualized Data Center

Resource allocation plays an important role inVirtualized Data Center (VDC). The applicationsrunning in VDC are mostly business criticalapplications with Quality-of-Service (QoS)requirements. Moreover, dynamic resource allocationand real time monitoring of the resource usage of VMsare also needed to reduce under resource utilization andover resource utilization. Therefore, resource usageprediction is required for dynamic resource allocationsystems. In efficient dynamic resource allocation, theresources are allocated to a VM while meeting theirService Level Agreement (SLA). The main contributionof this work is two-fold. The first is the generation ofCPU usage prediction models by applying differentpowerful machine learning techniques. The second isSLA evaluation on predicted value by using proposedSLA metric. To evaluate the efficiency of these models,experiments are carried out by using CPU profiles fromreal world data centre. According to the experiments,proposed resource prediction models have promisingaccuracy

Enhancing NameNode Fault Tolerance in Hadoop Distributed File System

In today’s cloud computing environment, Hadoop is applied for handling huge data, tens of terabytes to petabytes, with commodity hardware (HDFS) for storage and software (MapReduce) for parallel data processing. In Hadoop version 1.0.3, there is a single metadata server called NameNode which stores the entire file system metadata in main memory and most of I/O operations are associated with those credential metadata. Hadoop is out of commission if NameNode is crashed because it works on memory which becomes exhausted due to multiple concurrent accesses [3]. Therefore, NameNode is a single point of failure (SPOF) in Hadoop and it has to tolerate faults. To solve this issue, a proactive predictive solution is proposed for enhancing NameNode fault tolerance. The solution is designed to proactively calculate the predicted time to crash of NameNode due to resource exhaustion by evaluating the use of powerful Back Propagation Algorithm Neural Network. The proposed approach can give prediction accuracy with minimal error compared to the actual result. Therefore, NameNode’s single point of failure can overcome through proposed proactively predicting the time to crash of NameNode caused by memory resource exhaustion

Local Aggregation with Modified B+ tree in Map Reduce Data Processing

MapReduce is well-applied in high performance computing for large scale data processing. However, as long as the clusters grow, handling with huge amount of intermediate data produced in the shuffle and reduce phases (middle step of Map Reduce) have impacts heavily upon the performance. With local aggregation (either combiners or in-mapper), shuffling large amounts of data can be reduced which alleviates the reduce straggler problem. The proposed modified B+ tree based indexing algorithm is applied to reduce intermediate data amount for output retrieval fast as well as scalable data storage

Myanmar Compound Word Errors Detection and Suggestion Generation

In Myanmar Language, Pronunciation andorthography has differences because spelling is oftennot an accurate reflection of pronunciation.Pronunciation of a word may lead to misspelling. In thispaper, we present Myanmar Compound misused wordserrors detection and suggestion generation system. Inthis paper, we propose Myanmar compound misusedword error detection algorithm to apply in Myanmarspell checker. After detecting Myanmar compoundmisused words errors, we provide suggestion list, whichimplemented with two methods: Cosine Similarity andLevenshtein Distance Algorithm. To evaluate theefficiency of the system, we tested with various types ofMyanmar sentences which contain various types of spellerrors. According to the evaluation results, our proposedsystem achieves promising accuracy (over 90 %) forMyanmar compound misused words errors detection. Byanalyzing these two results, we found that LevenshteinDistance Algorithm can provide better relevantsuggestion list

Investigation of Android Device for Discovering Hadoop Cloud Storage Artifacts

Hadoop Cloud Storage has been embraced byboth individuals and organizations as it can offercost-effective, large capacity storage and multifunctionalservices on a wide range of device. It isfast raising popularity to access Hadoop Cloudservices via Android device. The widespread usage ofHadoop Cloud Storage could create the environmentthat is potentially conducive to malicious activitiesand illegal operations. Thus, the investigation ofHadoop Cloud presents the emerging challenge forthe digital forensic community. Extracting residualartifacts from the cloud server is potentially difficultdue to privacy policies followed by cloud providers.The attached Android device may store usefulartifacts to investigate the illegal usages of HadoopCloud Storage. This paper utilizes ClouderaDistribution Hadoop (CDH); a popular HadoopCloud Storage. This paper conducts a preliminaryinvestigation to locate and extract the residualartifacts from Android device that has accessed theCDH Cloud. The extracted artifacts can assist theforensic examiners in real world Hadoop Cloudforensics. The crime scenario which is extended theForensic Copra’s crime case is examined under theguide of CDH Forensic Investigation Framework

Availability Analysis on Virtualized Two-Node Cluster System: Ratio of Restoration Rate and Failure Rate

Worldwide, businesses continually increasetheir dependence on IT systems for routine businessprocesses. The business processes which directlyrely on information systems and the supporting ITinfrastructure often require high levels ofavailability and recovery in the case of plannedand unplanned outage. High availability hasachieved by host per host redundancy, a highlyexpensive method with hardware and human costs.Virtualization technologies promise cost reductionthrough resource consolidation. By combiningvirtualization and HA clustering, it is possible tobenefit from increased manageability and savingfrom server consolidation through virtualizationwithout decreasing uptime of critical services.Using analytical modeling, we analyze multipledesign choices when dual physical servers are usedto host multiple virtual machines. We use Markovdecision process when we are concerned aboutoptimal decision at any arbitrary time. Numericalexamples are presented to illustrate theapplicability of the model