WiMAX or Worldwide Interoperability for Microwave Access is a coalition of the wireless industry for the advancement of IEEE 802.16 standards for broadband wireless access (BWA) networks. WiMAX (Pareit et al., 2012) is commonly known as 4G network and is a wireless wide area network (WAN) that can cover the area same as DSL lines but without wires. 3DES (Data Encryption Standard) (Singh, 2013) and AES (Advanced encryption standard) (Ahmad & Ismail, 2016) is used by WiMAX to encrypt the data transferred on the network. The 3DES uses three different keys to encrypt the data. Each data is of the length of 56-bits each. In some software’s the performance becomes slow due to the use of this three keys. The 3DES is becoming obsolete due to its slow performance and the limit of length of the keys. Advanced Encryption Standard (Rewagad & Pawar, 2013) is the main tool used for encryption in WiMAX technology. Encryption key of 128-bit, 192-bit and 256-bit is supported by the advanced encryption standard. AES is a popular algorithm which was built from CCMP. 3DES is much slower than AES. Advanced Encryption standard is much more easy to implement and a very little memory is used. However, AES does not require dedicated processors on board the BS, and m their might be a risk of not being used by all end-user terminals. Initially this helps in considering the fact that 3DES still remains a vital encryption tool on the WiMAX (Dadhich, Narang & Yadav 2012) network in spite of the presence of advanced encryption standard.
The most common WAPN technology are the Bluetooth and the ZigBee network. Both this technology faces the same difficulty as that of the security issues faced by the wireless technology.
This article discusses about the energy harvesting techniques used in daily lives. Harvesting of energy is one of the emerging technology related to applications on indoor and outdoor environment. The demands for energy harvesting as increasing with the advancement of microelectronics and MEMS. This rep article also discusses about the problems and applications of energy harvesting. This has gained the attention of various stallholders which involves designs and implementation of this technology to face the energy demands of future wireless sensor networks. Moreover, this article focuses on the techniques required to meet the future energy demands of the WSNs. Specifically, this focuses on the classifications of the schemes used on energy harvesting techniques in WSNs. The article has thoroughly reviewed the classes and sub classes of energy harvesting techniques and the harvester mechanism along with the efficiency of the harvester. For each category the harvester hardware system has different design and has different harvesting capabilities. The different designs of the harvester determine the efficiency of the harvester. A survey has been conducted on various models aimed to predict the future energy cycles. The survey has proved that only few predictions technique has been used still far to in the area of modeling which states that the state-of-the-art is still immature. Addressing of several open research challenges still need to be done in the future which includes the need to focus on the miniaturized generic harvesters. This can later be used in different environments with energy sources that are dynamic. Major reason for deploying energy harvesting technique is due to the major problem faced by WSN regarding energy. In cases if the energy the sensor nodes depletes then the role is no longer played, unless and until a new source of energy is used or no other harvesting technique hasn’t been introduced to fulfill the energy gap.
Ulukus, Sennur, et al. "Energy harvesting wireless communications: A review of recent advances." IEEE Journal on Selected Areas in Communications 33.3 (2015): 360-381. 4.
This article summarizes the application of energy harvesting in a broad area of wireless communication network. This article has covered a variety of topics which includes the information-theoretical and physical layer of performance limit to the scheduling policies and medium access control protocol. This article also discusses about the emerging model of energy transfer and cooperation that occurs with the information transfer of the wireless network. The article has also presented a model of total energy consumption. The threats faced by energy harvesting from physical and practical concerns has made this technique face new challenges. Taking practical conditions mathematical formulas are designed which increases the set of possibilities. The discussion of the energy and information transfer provides exciting possibilities that can be adapted in the future to adapt the network operations with improved performance.
Ahmad, R., & Ismail, W. (2016). Performance Comparison of Advanced Encryption Standard-128 Algorithms for WIMAX Application with Improved Power-Throughput. Journal of Engineering Science and Technology, 11(12), 1-17.
Bahl, N., Sharma, A. K., & Verma, H. K. (2012). On Denial of Service Attacks for Wireless Sensor Networks. SYSTEM, 17, 18.
Dadhich, R., Narang, G., & Yadav, D. M. (2012). Analysis and Literature Review of IEEE 802.16 e (Mobile WiMAX) Security. International Journal of Engineering and Advanced Technology, 1, 167-173.
Ketari, L., & Khanum, M. A. (2012). A review of malicious code detection techniques for mobile devices. International Journal of Computer Theory and Engineering, 4(2), 212.
Olawumi, O., Haataja, K., Asikainen, M., Vidgren, N., & Toivanen, P. (2014, December). Three practical attacks against ZigBee security: Attack scenario definitions, practical experiments, countermeasures, and lessons learned. In Hybrid Intelligent Systems (HIS), 2014 14th International Conference on (pp. 199-206). IEEE.
Pareit, D., Lannoo, B., Moerman, I., & Demeester, P. (2012). The History of WiMAX: A Complete Survey of the Evolution in Certification and Standardization for IEEE 802.16 and WiMAX. IEEE Communications Surveys and Tutorials, 14(4), 1183-1211.
Ramsey, B. W., Mullins, B. E., & White, E. D. (2012, October). Improved tools for indoor ZigBee warwalking. In Local Computer Networks Workshops (LCN Workshops), 2012 IEEE 37th Conference on (pp. 921-924). IEEE.
Rawat, D. B., & Bhattacharya, S. (2016). Wireless Body Area Network for Healthcare Applications. In Advanced Methods for Complex Network Analysis (pp. 343-358). IGI Global.
Rewagad, P., & Pawar, Y. (2013, April). Use of digital signature with diffie hellman key exchange and AES encryption algorithm to enhance data security in cloud computing. In Communication Systems and Network Technologies (CSNT), 2013 International Conference on (pp. 437-439). IEEE.
Saliou, D. A., Al-Khateeb, W. F. M., Olanrewaju, R. F., & Fatai, S. Dual Authentication For Bluetooth Connection.
Shaikh, F. K., & Zeadally, S. (2016). Energy harvesting in wireless sensor networks: A comprehensive review. Renewable and Sustainable Energy Reviews, 55, 1041-1054.
Singh, G. (2013). A study of encryption algorithms (RSA, DES, 3DES and AES) for information security. International Journal of Computer Applications, 67(19).
Ulukus, S., Yener, A., Erkip, E., Simeone, O., Zorzi, M., Grover, P., & Huang, K. (2015). Energy harvesting wireless communications: A review of recent advances. IEEE Journal on Selected Areas in Communications, 33(3), 360-381.
Vidgren, N., Haataja, K., Patino-Andres, J. L., Ramirez-Sanchis, J. J., & Toivanen, P. (2013, January). Security threats in ZigBee-enabled systems: vulnerability evaluation, practical experiments, countermeasures, and lessons learned. In System Sciences (HICSS), 2013 46th Hawaii International Conference on (pp. 5132-5138). IEEE.
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