iosr-JCE   Volume-17 ~ Issue-2 ~ March-April 2015

Abstract: In this paper, we propose a Multihop Multi-Channel Distributed QoS Scheduling MAC scheme (MMDQS-MAC) to improve the network performance of WSNs, which selects the best channel for an individual wireless sensor node. MMDQS-MAC supports dynamic channel assignment mechanism where each sensor node is equipped with a directional antennas. The proposed protocol helps to decrease the probability of collision, interferences and improves the overall network performance of Wireless Sensor Networks (WSNs). The protocol is most suitable for short packet transmission under low traffic networks and has ability to utilize parallel transmission among neighboring nodes and achieves increased energy efficiency when multi-channels are available. Simulation result shows that the proposed protocol improves the performance of aggregate throughput, probability of successful transmission, packet delivery ratio, energy consumption and average end-to-end delay.

Keywords: Medium Access Control (MAC); Quality of Service (QoS); Wireless Sensor Networks (WSNs); Multi-Channel (MC)

[1]. Stallings and William, "Wireless Communications and Networks," Second Edition New Jersey, Pearson Education International,
2005.
[2]. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, "A Survey on Sensor Networks," In IEEE Communicatio n
Magazine, vol. 40, no. 8, pp. 102–114, August 2002.
[3]. D. Cruller, D. Estrin and M. Srivastava, "Overview of Sensor Networks," In IEEE Computer, vol. 37, no. 8, pp. 41 –49, August
2004.
[4]. W. Ye, J. Heidemann and D. Estrin, "An Energy-Efficient MAC Protocol for Wireless Sensor Networks," In proceedings of 21st
IEEE INFOCOM, New York, pp. 1567–1576, June 2002.
[5]. F. Cuomo, A. Baiocchi and R. Cautelier, "A MAC Protocol for a Wireless LAN based on OFDM-CDMA," In IEEE
Communications Magazine, vol. 38, no. 9, pp. 152–159, September 2000.

Abstract: While email is fairly reliable, messages do get lost. This can be due to the store-and-forward nature of e- mail, which passes responsibility for delivering email from one mail server to another, but in doing so exposes messages to loss, should a server not fulfil its responsibility. Some end users are more sensitive to email unreliability than others, and seek tools with which they can detect and recover from email failures. This paper describes tools that allow email sending software to automatically respond to reports of undeliverability by persisting with retransmission or retransmitting to alternate recipients.

[1]. P. Lyman and H. Varian: "How Much Information", http://www.sims.berkeley.edu/how-much-info-2003
[2]. T. Moors: "Email reliability", http://uluru.ee.unsw.edu.au/~tim/dependable/email/
[3]. M. Afergan and R. Beverly: "The state of the email address", Computer Communication Review, 35(1):29- 35, Jan. 2005
[4]. S. Garriss, M. Kaminsky, M. Freedman, B. Karp, D. Mazihres and H. Yu: "RE: Reliable Email", Proc. NSDI, pp. 297-310, May 2006
[5]. J. Klensin: "Simple Mail Transfer Protocol," IETF, RFC 2821, Apr. 2001

Abstract: Mobile forensic is fast becoming an abbreviated term that describes the process of applying digital forensics in mobile phones world. The rapid development in mobile phones industry has led to the emergence of the so-called smart phones which have become nearly the same as computers. Android Smartphones refer to all types of smartphones that use Android operating system. This paper aims to survey the tools and techniques that are used to forensically investigate Android mobile and then provides comparison between the tools according to their roles in the investigation process. Finally, the paper gives recommendation for following the best practices for investigating Android smartphones.

[1]. A. Hoog, Android Forensics:Investigation, Analysis and Mobile Security for Google Android: Syngress, 2011.
[2]. L. ı. N. Claudio Maia, Lu´ıs Miguel Pinho. (2014, Evaluating Android OS for Embedded Real-Time Systems. Cyber Forensics.
[3]. E. H. S. Brian D. Carrier. 02/02/2015). An Event-Based Digital Forensic Investigation Framework. Available: http://www.digital-evidence.org/papers/dfrws_event.pdf
[4]. Android.com. (2014). History of Android. Available: http://www.android.com/history/
[5]. idc.com. Smartphones Market share , Q3 2014. Available: http://www.idc.com/prodserv/smartphone-os-market-share.jsp

Abstract: This paper discusses a propose cloud infrastructure that combines On-Demand allocation of resources with improved utilization, opportunistic provisioning of cycles from idle cloud nodes to other processes.Because for cloud computing to avail all the demanded services to the cloud consumers is very difficult. It is a major issue to meet cloud consumer's requirements. Hence On-Demand cloud infrastructure using Hadoop configuration with improved CPU utilization and storage utilization is proposed using splitting algorithm by using Map-Reduce. Henceall cloud nodes which remains idle are all in use and also improvement in security challenges and achieves load balancing and fast processing of large data in less amount of time. Here we compare the FTP and HDFS for file uploading and file downloading; and enhance the CPU utilization and storage utilization. Cloud computing moves the application software and databases to the large data centres, where the management of the data and services may not be fully trustworthy. Therefore this security problem is solve by encrypting the data using encryption/decryption algorithm and Map-Reducing algorithm which solve the problem of utilization of all idle cloud nodes for larger data.

Keywords: CPU utilization, Storage utilization, Map-Reduce,Splitting algorithm, Encryption/decryption algorithm.

[1]. Paul Marshall "Improving Utilization of Infrastructure Clouds",CO USA, IEEE/ACM Cloud Computing May 2011.
[2]. Shah, M.A., et.al., "Privacy-preserving audit and extraction of digital contents", Cryptology ePrint Archive, Report 2008/186 (2008).
[3]. Juels, A., Kaliski Jr., et al.; "proofs of retrievability for large files", pp. 584–597. ACM Press, New York (2007).
[4]. Aspera an IBM company (2014,07,14). Big Data Cloud[English].Available:http://cloud.asperasoft.com/big-data-cloud/.
[5]. Divyakant Agrawal et al., " Big Data and Cloud Computing: Current State and Future Opportunities" , EDBT, pp 22-24, March 2011.
[6]. The Apache Software Foundation(2014,07,14). Hadoop[English]. Available:http://hadoop.apache.org/.

Abstract:Blind signature is a concept to ensure anonymity of e-coins. Untracebility and unlinkability are ttwo main properties of real coins and should also be mimicked electronicaly. A user has fulfill above two properties of blind signature for permission to send an e-coins. During the last few years, asymmetric cryptography based on curve based cryptography have becomes very popular, especially for embedded applications. Elliptical curves cryptography (CC) are the special case of elliptical curves (EC). EC operand size is only a fraction of the EC operand Size. EC Cryptography needs a group order of size atleast 2160. In Particular for a cuve of genus two field Fq with p long operands. Which is much better than the RSA using 1024 bit key length. The elliptic curve is best suited for the resource constraint environment s. It uses lesser key and provides more secure transmission of data.
Index Terms: Hyperelliptic curve cryptography, proxy signature, Blind signature, symmetric key cryptography, Asymmetric cryptography.

[1]. Behrouz A Forouzan. Cryptography & Network Security. McGraw-Hill, Inc., 2007.
[2]. J. Pelzl, T. Wollinger, and C. Paar. High performance arithmetic for special elliptic curve cryptosystems of genus two. In International Conference on Information Technology: Coding Computing, ITCC, volume 2, pages 513–517, 2004.
[3]. Y. Lin, M. Wu, J. A. Bloom, I. J. Cox, and M. Miller, "Rotation, scale, and translation resilient public watermarking for images," IEEE Trans. Image Process., vol. 10, no. 5, pp. 767-782, May 2001.
[4]. Henri Cohen. Handbook of Elliptic and elliptic Curve Cryptography. CRC Press, Abingdon, 2005
[5]. Sunder Lal and Amit K Awasthi. Proxy blind signature scheme. 2003.
[6]. Masahiro Mambo, Keisuke Usuda, and Eiji Okamoto. Proxy signatures for delegating signing operation. In Proceedings of the 3rd ACM conference on Computer and communications security, pages 48–57. ACM, 1996.

Abstract: Multi Version Concurrency Control (MVCC) is a locking scheme commonly used by modern database implementations to control fast, safe concurrent access to shared data. MVCC is designed to provide the following features for concurrent access: a. Readers that don't block writersb. Writers that fail fastMVCC achieves this by using data versioning and copying for concurrent writers. The theory is that readers continue reading shared state, while writers copy the shared state, increment a version id, and write that shared state back after verifying that the version is still valid (i.e., another concurrent writer has not changed this state first). This allows readers to continue reading while not preventing writers from writing and repeatable read semantics are maintained by allowing readers to read off the old version of the state.

Keywords: Lock based protocols, Time stamp based protocols, Two phase Locking, Deadlock Avoidance, Remote DataBackup, Log Based Recovery, Multi-core Systems.

[1]. " A Secure Time-Stamp Based Concurrency Control Protocol For Distributed Databases" Journal of Computer Science 3 (7): 561-565, 2007

[2]. "Some Models of a Distributed Database Management System with Data Replication", International Conference on Computer Systems and Technologies - CompSysTech'07.

[3]. "A Sophisticated introduction to distributed database concurrency control", Harvard University Cambridge, 1990.

[4]. "Database system concepts",from Silberschatz Mc-graw Hill 2001.

[5]. P. Bernstein and N. Goodman. Multiversion Concurrency Control–Theory and Algorithms. ACM TODS, 8(4):465–483, 1983.

[6]. C. Bienia, S. Kumar, J. P. Singh, and K. Li. The PARSEC Benchmark Suite: Characterization and Architectural Implications. In PACT, PACT '08, 2008.

Abstract: It is used in designing of network architecture and computer resource. There is cloud of computers. Use of cloud network reduces the requirement of hardware and software.

Keywords: Cloud computing, Computer, Network, data breach, data authentication.

[1]. "Building GrepTheWeb in the Cloud, Part 1: Cloud Architectures". Developer.amazonwebservices.com. Retrieved 2010-08-22.

[2]. "Cloud Computing entry". NetLingo. Retrieved 15 January 2014.

[3]. University of Michiganhttp://it.umich.edu/initiatives/cloud/content/what-cloud. Retrieved 15 January 2014.

[4]. "The NIST Definition of Cloud Computing". National Institute of Standards and Technology. Retrieved 24 July 2011.

[5]. "What is Cloud Computing?". Amazon Web Services. 2013-03-19. Retrieved 2013-03-20.

Abstract: This paper proposes a novel method to monitor and control the network usage of a shared wireless connection. The main objective of this technique is to balance and restrict the shared network data. It facilitates monitor of data usage by each user individually. This technique is demonstrated through a user-friendly command line interface. The implementation is tested with Android Mobile Hotspot which exhibited satisfactory results as discussed in the paper.

Keywords: Batch Scripting, Command Line Interface, Data Usage Monitor, Limiting Data Usage, Network Profile, Windows Powershell, Windows Task Scheduler

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Abstract: The study were carried out at Arais area north Umkaddada town, the objective was to study the non wood forest products for their role in income generation, type of fruits, Grasses and other parts of trees available in the area and their contribution to income generation. The study showed that Grewia tenax, Baid grass, Acacia tortilis, Balanite aegyptiaca, Sclerocarya birrea and Ziziphus spini christi were the most subsidiary source and presented that the mother trees of the some species were highly affected. The study area lies eastern part of the State. It is geographically located within 12th and 15th degree of latitude N, 25th and 28th degree of longitude E. Covering an area of 40,000 squire km. It is bordered on the east by North Kordofan State, on the south by eastern Darfur State on north and west by Milliet and Ekoma localities respectively.

Key words: income generation, subsidiary source, Grewia tenax, Ziziphus spini christi, Adansonia degitata

[1]. Abdelmaji, T. D (2001). Biodiversity and its influences on non wood forest products.
[2]. Andrews, F. W, (1965). Flowering plants of Anglo Aegyptium Suda, Vol. 1-3.T. Buncle and co., Arbriath, Scotland.
[3]. IBGR, (1984). Forage and browse plants for arid and semi arid African International Board for plant Genetics Resource. Royal Botanical Garden, Kew London P11- 218.
[4]. FAO, (1992). Forest, Trees and Food, FAO, Rome. Rural small scale forest – based processing enterprises in Zambia, report of 1985 pilot study, FO, MISC/15. FAO, Rome.
[5]. FAO, (1991). Non-Wood Forest Products: The Way Ahead. Forestry Paper 97. FAO, Rome.

Abstract: Credit card is one of the convenient way of payment in online shopping. In this on line shopping, payment is made by giving information like card no, security code , expiration date of the Credit card etc . To rectify the risk factors of using the credit card, every card holder's spending method is modeled by using HMM. By using this authenticated security check the information of transaction is fraudulent or genuine. It is highly secured from unauthorized anomalous user using credit card and avoids fraud usage of card through online transactions.

Keywords: HMM, FDS, TP, FP

[1]. Ghosh, S., and Reilly, D.L., 1994. Credit Card Fraud Detection with a Neural-Network, 27th Hawaii International l Conference on Information Systems, vol. 3 (2003), pp. 621- 630.
[2]. Stolfo, S. J., Fan, D. W., Lee, W., Prodromidis, A., and Chan, P. K., 2000.Cost-Based Modeling for Fraud and Intrusion Detection: Results from the JAM Project, Proceedings of DARPA Information Survivability Conference and Exposition, vol. 2 (2000), pp. 130-144
[3]. R. Brause, T. Langsdorf, and M. Hepp, "Neural Data Mining for CreditCard Fraud Detection," roc. IEEE Int'l Conf. Tools with ArtificialIntelligence, pp. 103-106, 1999.
[4]. Aleskerov, E., Freisleben, B., and Rao, B., 1997. CARDWATCH: ANeural Network Based Database Mining System for Credit Card FraudDetection, Proceedings of IEEE/IAFE: Computational Intelligence forFinancial Eng. (1997), pp. 220-226.
[5]. W. Fan, A.L. Prodromidis, and S.J. Stolfo, "Distributed Data Mining inCredit Card Fraud Detection," IEEE Intelligent Systems, vol. 14, no. 6,pp. 67-74, 1999.
[6]. C. Phua, D. Alahakoon, and V. Lee, "Minority Report in FraudDetection: Classification of Skewed Data," ACM SIGKDD ExplorationsNewsletter, vol. 6, no. 1, pp. 50-59, 2004.

Abstract: The objective of the paper is to investigate the step response of a 2 DOF quarter-car model with passive suspension. The mathematical models of the sprung-mass displacement and acceleration as response to the step road disturbance are derived. The step response of the system is plotted using MATLAB for a 100 mm step amplitude. The effect of the suspension parameters on the step response of the sprung-mass is investigated in terms of motion displacement and acceleration. The maximum percentage overshoot and settling time of the step response are evaluated as time-based characteristics of the dynamic system for a specific range of the suspension parameters. The maximum acceleration of the sprung-mass due to the step road disturbance did not conform with the ride comfort requirements according to ISO 2631-1 standard .

Keywords: Car dynamics; quarter car model; passive suspension; step response, sprung-mass acceleration

[1]. J. Masi, Effect of control techniques on the performance of semiactive dampers, M. Sc. Thesis, Faculty of Virginia Polytechnic Institute and State University, December 2001.
[2]. O. Askerdal, M. Gafvert M. Hiller and N. Suri, Analyzing the impact of data errors in safety critical control systems, IEICE Transaction on Information and Systems, E86-D, No.12, 2623-2633, 2003.
[3]. Y. Toshio and T. Atsushi, Pneumatic active suspension system for a one wheel car model using fuzzy reasoning and disturbance observer, Journal of Zhejiang University Science, 5 (9), 1060-1068, 2004.
[4]. L. Sakman, R. Guclu and N. Yagiz, Fuzzy logic control of vehicle suspension with dry friction nonlinearity, Sadhana, 30 (5), 649-659, 2005.
[5]. A. Faheem, F. Alam and V. Thomas, The suspension dynamic for a quarter-car model and half-car model, 3rd BSME-ASME International Conference on Thermal Engineering, 20-22 December, Dhaka, 2006.
[6]. M. Maila and G. Priyandoko, Simulation of a suspension system with adaptive fuzzy active force control, International Journal of Simulation Modeling, 6 (1), 25-36, 2007.

Abstract: Cloud computing facilitates the owners to share data. Multiple parties join the learning process by conducting joint Back propagation neural network algorithm on the union of their respective data sets. During the learning process none of the party wants to disclose her/his private data to others. The limitations of the existing schemes are learning process for only two parties or the few ways in which the data is arbitrarily partitioned. The proposed solution allows two or more parties, each with an arbitrarily partitioned data set, to jointly conduct the learning. The solution is provided by the magnificent power of cloud computing. In the proposed scheme, each owner encrypts his/her private dataset locally through AES cryptography and uploads the cipher texts into the cloud. The cloud then executes most of the operations over cipher texts via BGN homomorphic algorithm. The cloud is unaware of the original dataset. The Back propagation learning takes place and the owners are benefited through collaborative learning. Thus the scalability of the learning process is improved and the privacy of the data is ensured.

Keywords: Privacy preserving, learning, neural network, back-propagation, cloud computing, computation outsource, homomorphic encryption

[1]. "The Health Insurance Portability and Accountability Act of Privacy and Security Rules," http://www.hhs.gov/ocr/privacy, 2013.
[2]. "National Standards to Protect the Privacy of Personal Health Information," http://www.hhs.gov/ocr/hipaa/finalreg.html, 2013.
[3]. M. Abramowitz and I.A. Stegun, Handbook of Mathematical Functions: With Formulas, Graphs, and Mathematics Tables, DoverBooks on Mathematics. Dover, 1964.
[4]. A. Bansal, T. Chen, and S. Zhong, "Privacy Preserving Back-Propagation Neural Network Learning over Arbitrarily Parti-tioned Data," Neural Computing Applications, vol. 20, no. 1, pp. 143150,Feb. 2011.
[5]. D. Boneh, E.-J. Goh, and K. Nissim, "Evaluating 2-DNF Formulas on Ciphertexts," Proc. Second Int‟l Conf. Theory of Cryptography (TCC ‟05), pp. 325-341, 2005.
[6]. T. Chen and S. Zhong, "Privacy-Preserving Backpropagation Neural Network Learning," IEEE Trans. Neural Network, vol. 20, no. 10, pp. 1554-1564, Oct. 2009.

Abstract:Removal of random valued impulse noise in digital images with edge preservation is one of the challenging tasks in digital image processing. For removal of impulse noise as well as preserve edge proposed a new filter that is Dual Threshold Median Filter (DTMF). The removal of impulse noise is done in two main stages, firstly, the detection of the impulse noise on the basis of maximum and minimum value of pixels in a 3X3 window. In the second stage, removal of impulse noise by using of median filter. In the filtering stage, the noisefree pixels remain unchanged in the low noise density, but in case of high noise density that is very difficult of identify the noisy pixel or edge of the image, this difficulty is remove by our proposed filter. The experimental outcome of our proposed filter is superior to the previous methods in terms of Peak Signal Noise Ratio and Mean Square Error of the different testing images, with different noise density level. The mathematical analysis describes that the analysis of the noisy pixels and use of noise-free pixels for the de - noising purpose provide better results and provides better visual quality of de-noised image.
Keywords: Dual Threshold, Random Valued Impulse Noise, Visual quality, Bluer

[1]. Zhu Youlian, Huang Cheng, "An Improved Median Filtering Algorithm Combined with Average Filtering", IEEE, 2011 Third International Conference on Measuring Technology and Mechatronics Automation, 6-7 Jan. 2011, pp. 420 – 423.
[2]. Vikas Gupta and Abhishek Sharm "Image De-Noising by Enhanced MedianFiltering for High Density Noisy Images" Springer 2013 Fourth International Conference onSignal and Image Processing 2012 ICSIP. DOI: 10.1007/978-81-322-1000-9_55.
[3]. WANG Chang-you, YANG Fu-ping, GONG Hui, A new kind of adaptive weighted median filter algorithm, 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).
[4]. Gonzalez R.C, Woods. R.E., Digital Image Processing, 3rd edition, Pearson Prentice Hall, 2009.
[5]. Shanmugavadivu P & Eliahim Jeevaraj P S, "Laplace Equation based Adaptive Median Filter for Highly Corrupted Images", International Conference on Computer Communication and Informatics (ICCCI -2012), 2012
[6]. T.-C. Lin, P.-T. Yu, , A new adaptive center weighted median filter for suppressing impulsive noise in images, Information Sciences 177 (2007) 1073–1087.

Abstract: Research in e-voting aims at designing usable and secure electronic voting systems. This paper provides an empirical analysis of the computational performance of a prototype implementation of the Bingo electronic voting protocol. Bingo is a receipt-based end-to-end verifiable electronic voting protocol that claims the property of coercion resistance. According to this work, a prototype of the Bingo design has been described in terms of sequence and class diagrams. Also, its operation has been demonstrated using a case study of a sample election. Four main operations have been analyzed; initialization of cyclic groups, generation of dummy votes, zero-knowledge proof of fair vote distribution over candidates, and zero-knowledge proof of receipt correctness. The performance was affected by the cyclic group order, number of candidates, and number of voters.

Keywords: E-voting, Bingo voting, coercion resistance, zero-knowledge proof, commitments.

[1]. R. Jardí-Cedó, J. Pujol-Ahulló, J. Castellà-Roca, and A. Viejo, "Study on poll-site voting and verification systems," vol. 31, no. 8, pp. 989-1010, 2012.
[2]. M. F. Mursi, G. M. Assassa, A. Abdelhafez, and K. M. Abo, "On the Development of Electronic Voting: A Survey," vol. 61, no. 16, pp. 1-11, 2013.
[3]. R. Küsters, T. Truderung, and A. Vogt, "A game-based definition of coercion resistance and its applications," vol. 20, no. 6, pp. 709-764, 2012.
[4]. L. AhmedQubati, S. Khattab, and I. Farag, "Survey on End-to-End Verifiable Cryptographic Voting Systems," vol. 100, no. 16, pp. 43-57, 2014.
[5]. A. J. Menezes, P. C. Van Oorschot, and S. A. Vanstone, Handbook of applied cryptography: CRC press, 2010.

Abstract: Internal transcribed spacer is a special sequence that present in between sequence of ribosomal DNA. It is present in multiple copies and act as a conservative sequence. This sequence is unique for particular living being there for it is used as tool for identification.Present study carried out to identification of floral degrading fungi by using of PCR method. This process was done with the help of specific primer. The length of primer was different for different group of fungi. There were four fungi which identified were Aspergillus flavus, A. fumigatus, A. terrus and Alternaria alternate.

Key words: ITS, PCR, vermicomposting, rDNA, electrophoresis.

[1]. BioAxis DNA Research Centre Private Limited. (Report Reference:13/FNG/SEQ/RREL-08/902) (Samflople ID: DMB/08/13/902)
[2]. Timberlake, W. E. & Marshall, M. A. Genetic engineering of filamentous fungi. Science 244, 1313–-1317 (1989).
[3]. Hibbett DS (1992). Ribosomal RNA and fungal systematics. Trans. Mycol. Soc. 33: 533-556.
[4]. Bruns TD, White TJ, talyor JW (1991). Fungal molecular systematics. Annu. Rev. Ecol. Sys. 22: 525-564.
[5]. Bryan GT, Daniels MJ, Osbourn AE (1995). Comparison of fungi within the Gaeumannomyces-Phialophora complex by analysis of ribosomal DNA sequence. Appl. Environ. Microbiol. 61: 681-689.
[6]. Taiwo , L. B. and Oso, B. A.(2004) Influence of composting techniques on microbial succession, temperature and pH in a composting municipal solid waste. African Journal of Biotechnology. 3(4):239-243.