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Santhi, B.
- Study on Features, Statistics, and Security Measures of Portable Operating System
Abstract Views :330 |
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Authors
Affiliations
1 ICT, School of Computing, SASTRA University, Tirumalaisamudram, Thanjavur, Tamil Nadu
1 ICT, School of Computing, SASTRA University, Tirumalaisamudram, Thanjavur, Tamil Nadu
Source
Indian Journal of Science and Technology, Vol 6, No 6 (2013), Pagination: 4678-4682Abstract
With the increase in memory space and the need for smarter and portable computing devices, the risk for information security also increases. Comparing this with open source and portable software the life is made even easier and other extent the threat has also evenly increased. This paper briefly explains the different kinds of portable operating system available, their performance, memory usage, and applications they support and finally risk involved in using such operating system. It also portrays the comparison between some of USB operating system and explains the field where it can be applied. The threats governing the portable operating system is brought in to discussion and the security measures required to prevent the threat is also discussed.Keywords
POS-Portable Operating System, OS-Operating System, USB-Universal Serial Bus, DOS-Disk Operating System, BASIC-Beginner's All-purpose Symbolic Instruction Code, POSIX-Portable Operating System Interface, BSD-Berkeley Software DistributionReferences
- Polsson K (2008). A Brief Timeline of Personal Computers, Online, Available From: http://www.islandnet.com/~KPOLSSON/comphist/mini.htm
- DUX Computer Digest: Hard Disk Drive Guide, A Brief History of the Hard Disk, Online, Available From: http://www.duxcw.com/digest/guides/hd/hd2.htm
- Hyslip T (2008). Thyslip Portable Operating System, Online, Available From: http://www.infosecwriters.com.
- Sammett J E (1969). Programming languages: history and fundamentals, Prentice Hall.
- Available From: http://en.wikipedia.org/wiki/Live_USB
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- EECDC: Energy Efficient Coverage Aware Data Collection in Wireless Sensor Networks
Abstract Views :325 |
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Authors
Affiliations
1 SASTRA University, Department of Computer Science Engineering, IN
1 SASTRA University, Department of Computer Science Engineering, IN
Source
Indian Journal of Science and Technology, Vol 6, No 7 (2013), Pagination: 4903-4907Abstract
Energy efficient head node selection is the major issue in wireless sensor networks. Due to irregular node distribution energy consumption is not a balanced one in cluster-based wireless sensor networks. The proposed system provides techniques to rectify this problem through: (i) Forming Maximal Independent Set (MIS) (ii) Effective Set Head selection (iii) Multi-hop communication. Non adjacency of nodes has been leveraged for creating MIS. Intra-set energy consumption has been reduced by selecting a node as Set Head (SH), which is geographically nearer to all other nodes. Inter Set efficient energy consumption is achieved by using multi-hop communication between SH to BS. The proposed system EECDC forms more efficient and stable sets, which increases the lifetime of sensor networks i.e., Number of data collection rounds.Keywords
Energy Efficient, Maximum Independent Set (MIS), Coverage, Wireless Sensor NetworksReferences
- Baranidharan B, and Santhi B (2012). EEGTP: Energy efficient graph theory protocol for wireless sensor networks, Information Technology Journal, vol 11(7), 808–811.
- Ye F, Zhong G et al. (2003). PEAS: A robust energy conserving protocol for long-lived sensor networks, Proceedings of the 23rd International Conference on Distributed Computing Systems (ICDCS’03), 28–37.
- Jia J, Chen J et al. (2009). Energy efficient coverage control in wireless sensor networks based on multi-objective genetic algorithm, Computers & Mathematics with Applications. vol 57(11–12), 1756–1766.
- Yu J, Qi Y et al. (2012). A cluster–based routing protocol for wireless sensor networks with nonuniform node distribution, AEU–International Journal of Electronics and Communications, vol 66(1), 54–61.
- Shahzad K, Ali A et al. (2008). ETSP: An energy-efficient time synchronization protocol for wireless sensor networks, 22nd International Conference on Advanced Information Networking and Applications–Workshops, DOI 10.1109/WAINA.2008.181, 971–976.
- Liu M, Cao J N et al. (2007). An energy-aware data gathering protocol for wireless sensor networks, Journal of Software, vol 18(5), 1092–1109.
- Jha M K, Kumar A et al. (2011). An energy-efficient multi-layer MAC (ML-MAC) protocol for wireless sensor networks, AEU–International Journal of Electronics and Communications, vol 65(3) 209–216.
- Dimokas N, Katsaros D et al. (2010). Energy–efficient distributed clustering wireless sensor network, Journal of Parallel and Distributed Computing, vol 70(4), 371–383.
- Pantazis N A, Vargados D J et al. (2009). Energy efficiency in wireless sensor networks using sleep mode TDMA Scheduling, Ad Hoc Networks, vol 7(2), 322–343.
- Lindsey S, Raghavendra C S (2002). PEGASIS: Power efficient gathering in sensor information systems, IEEE Aerospace Conference Proceedings. vol 3, 3–1125–3–1130.
- Jang U, Lee S et al. (2012). Optimal wake-up scheduling of a data gathering trees for wireless sensor network, Journal of Parallel and Distributed Computing, vol 72(4), 536–546.
- Heinzelman W, Chandrakasan A et al. (2000). Energy-efficient communication protocol for wireless microsensor networks, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, 2000.
- Tan W L, Lau W C et al. (2012). Performance analysis of an adaptive energy-efficient MAC protocol for wireless sensor network, Journal of Parallel and Distributed Computing, vol 72 (4), 504–514.
- Ye W, Heidemann J et al. (2002). An energy-efficient MAC protocol for wireless sensor networks, Proceedings, IEEEINFOCOM 2002, Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies, vol 3, 1567–1576.
- Wu W, Du H et al. (2006). Minimum connected dominating sets and maximal independent sets in unit disk graphs, Theoretical Computer Science, vol 352 (1–3), 1–7.
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- Energy Efficient Hierarchical Unequal Clustering in Wireless Sensor Networks
Abstract Views :177 |
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Authors
Affiliations
1 Department of Computer Science Engineering, SASTRA University, IN
2 Advanced Computing, SASTRA University, IN
1 Department of Computer Science Engineering, SASTRA University, IN
2 Advanced Computing, SASTRA University, IN
Source
Indian Journal of Science and Technology, Vol 7, No 3 (2014), Pagination: 301–305Abstract
Energy efficient modeling is a major issue in the wireless sensor network. The main solution for energy efficient routing is by means of clustering. This paper proposes an unequal clustering approach in the networks for even energy distribution. It also reduces the overall energy consumption which in turn improves the network lifetime. The simulation is carried out in MATLABR2010a. The energy needed for entire operations for one round using the proposed method is lesser than that of LEACH, an equal clustering methodology.Keywords
Clustering, Energy Efficient, Unequal Clustering- Attribute Based Spanning Tree Construction for Data Aggregation in Heterogeneous Wireless Sensor Networks
Abstract Views :112 |
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Authors
Affiliations
1 School of Computing, SASTRA University, Thanjavur, Tamil Nadu- 613401, IN
1 School of Computing, SASTRA University, Thanjavur, Tamil Nadu- 613401, IN
Source
Indian Journal of Science and Technology, Vol 7, No S5 (2014), Pagination: 76-79Abstract
Wireless sensor network consists of densely deployed sensor nodes which have limited resources like energy, node lifetime. Data aggregation is an effective scheme to reduce redundancy of sampled data generated by sensor nodes. Homogeneous sensor networks easily adapt the data aggregation scheme because of easy synchronization of data samples; but heterogeneous sensor network have difficulty to handle data aggregation due to synchronization of different data packets produced by different sensor nodes. In order to perform efficient data aggregation in heterogeneous sensor networks our proposed method Attribute based Spanning Tree (AST) introduced the method of attribute based spanning tree construction over heterogeneous networks. Based on the characteristics of sensor nodes, logical separation of nodes formed then each group constructs Minimum Spanning Tree (MST), aggregation follows this MST to reach sink node. By adapting Kruskal's algorithm into our proposed method MST is constructed in sensor nodes. Our simulation results shows that AST is more spatially convergent and it uses shortest path cost for aggregation leads to increase node lifetime and saves energy.Keywords
Data Aggregation, Heterogeneous Sensor Networks, Spanning Tree- Enhancement of Information Hiding in Audio Signals with Efficient Lsb Based Methods
Abstract Views :127 |
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Authors
Affiliations
1 School of Computing, SASTRA University, Thanjavur, Tamil Nadu- 613401, IN
1 School of Computing, SASTRA University, Thanjavur, Tamil Nadu- 613401, IN
Source
Indian Journal of Science and Technology, Vol 7, No S5 (2014), Pagination: 80-85Abstract
In the modern era the easiness in the content alteration and copying in an available digital domain have enriched the security of academic copyrights as well as the anticipation of the illegal inference of data of multimedia have turned into a significant research and technological issue. Steganography is called as an art of secret and secured communication. The basic idea behind this paper is to find the best way to embed text data in audio file using the steganography techniques. Our proposed method uses LSB technique only in specific bit positions which are known only to sender and receiver. Our results have shown that the quality of the audio remains same after embedding the secret text and also very less difference between the original audio and steganographed audio. These results were obtained by the estimation of PSNR, MSE and audio features such as Pitch, Entropy and Flatness etc. The size of the audio signal also remains unaltered.Keywords
Information Hiding, LSB, MSE, PSNR, Stegnography- Efficient Clustering for Wireless Sensor Networks using Evolutionary Computing
Abstract Views :134 |
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Authors
A. R. Revathi
1,
B. Santhi
1
Affiliations
1 School of Computing, SASTRA University, Thanjavur, Tamilnadu, 613402, IN
1 School of Computing, SASTRA University, Thanjavur, Tamilnadu, 613402, IN