Technologies Smart Applications Of Energy Essay

Question:

Discuss About The Technologies Smart Applications Of Energy?

Answer:

Introducation

Three data encryption standards that are used by WiMax networks are 3DES, AES and PKMv2. These standards of techniques help WiMax to keep security on its networks.

3DES is the encryption standard that is officially known as Triple Data Encryption Algorithm (Zhang et al., 2014). This 3DES is a symmetric key block cipher which uses the Data Encryption Algorithm three times for a particular block of data. The key size of cipher of the Data Encryption Algorithm is 56 bit. But increasing amount of computational power made the DES security at risk. The key size of the 3DES is increased to make the DES encryption standard more secure to provide protection against all the data security attack by transforming the data into a new block of data.

The second standard of WiMax is the Advanced Encryption Standard (AES) which is a block of cipher that is symmetric to give protection to the classified data and the Advanced Encryption Standard is implemented in hardware and software so that the data that are sensitive will be encrypted (Usman & Shami, 2013). National Institute of Standards and Technology mentioned that this algorithm must have a capability to handle 128 blocks of data with a key size of 128 bits, 192 bits and also 256 bits. The criteria that are followed by the AES Standard are: Security- The security of the data is to be looked after so that they are not hacked by hackers. Ciphers are to be added in the original text so that the changed data do not get hacked. Cost- The cost of Advanced Encryption Standard is much less than other standards of algorithm that provides security to the data encryption process. Implementation- AES standard of data encryption has an implementation process that provides sustainability to the algorithm.

The most important encryption standard that is followed by WiMax is the process of Private Key Management version 2. The WiMax provides support to all the users. The key distribution is secured in PKMv2 standard technique with the EAP (Extensible Authentication protocol). Handovers may create packet lose and delay of data which affects the communication performance of the real time (Hassan & Bach, 2014). So to mitigate this problem, new process of key caching PKMv2 is introduced to introduce the processing time and authentication cost of the data encryption. The process helps to investigate the process and also stimulates the network entry process by the implementation of MATLAB model with structured Query Language attached to it. The network simulator carries the simulation. PVMv2 has three types of caching techniques that are used in key encryption.

The two examples of WPAN (Wireless Personal Area Network) Technology are Zigbee or Z-Wave and Bluetooth (Al-Fuqaha et al., 2015). There are many more examples of Wireless Personal Area Network such as Wi-Fi, INSTEON, Wireless USB, Body Area Network, IrDA. The security challenges of two examples of Wireless Personal Area Network that are explained are Zigbee and Bluetooth.


The security challenge of Zigbee or Z-Wave is that the signals of the Zigbee or Z-wave are not directly compatible with computing devices of mainstream like tablet, laptop and smart phone (Rault, Bouabdallah & Challal, 2014). The motion sensors or the bulbs are needed to communicate with hub which is connected to the Wi-Fi or the home network or via Ethernet cable that is plugged in the Internet router. The Hue bulbs work in this process. All the lights and bulbs of the house that are automated are connected to Zigbee hub which connects to Internet router. Zigbee and Z-wave are emerged together so that they are connected with the application of the phones or tablets. Zigbee or Z-wave is not compatible with each other which create a security challenge for the device.

The second example of Wireless Personal Area Network is Bluetooth that faces security challenge in the sector. The Bluetooth hacking is known as Bluesnarfing. The reason that lies behind Bluesnarfing is that the way in which Bluetooth is implemented on phones and tablets. In the case of Bluesnarfing, the process of object exchange protocol (OBEX) is implemented. Another process of Bluetooth hacking is the backdoor hacking (Tsampasis et al., 2016). This backdoor hacking occurs where the device is not trusted anymore and the mobile phone is accessed by hackers. This also gains access to the data with Bluesnarfing and uses services like Wireless Personal Area Network. Another process to hack Bluetooth is Bluebugging. This process helps to hack the mobile phones of the user. This attack is the most dangerous attack among all the attack that persists in Bluetooth. The hackers get control on the user’s phone and are able to read or send messages from the victim’s phone, monitor the phone calls, make calls from the phone and are able to all the stuffs that Bluesnarfing cannot do.

Article: “Energy harvesting in wireless sensor networks: A comprehensive review” and “Energy harvesting wireless communications: A review of recent advances”.

Energy Harvesting that is based on wireless sensor network is (EHWSN) the process of extracting energy from the environment that it is surrounded by (Shaikh & Zeadally, 2106). The different sources of energy can be exploited by energy harvesting that includes wind, temperature, magnetic fields and solar power. The process of providing energy continuously and storing the energy for future use is done by energy harvesting. The nodes of wireless sensor network so that they can last forever are enabled by energy harvesting systems. There are mainly two types of energy harvesting systems: energy harvesting that is done from the ambient sources which includes radio frequency based energy harvesting which involves RFID frequency for its application, solar based energy harvesting which involves solar energy storing for its future use, thermal based energy harvesting involves energy that come from the thermal source of energy and flow based energy harvesting are energy that comes from the rotors and turbines; and the external based energy harvesting are mechanical based and human based energy harvesting (Ulukus et al., 2015). The energy that is captured and stored for future use is the process of energy harvesting.

References

Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Communications Surveys & Tutorials, 17(4), 2347-2376.

Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. V., Lozano, A., Soong, A. C., & Zhang, J. C. (2014). What will 5G be?. IEEE Journal on selected areas in communications, 32(6), 1065- 1082.

Fagbohun, O. (2014). Comparative studies on 3G, 4G and 5G wireless technology. IOSR Journal of Electronics and Communication Engineering, 9(3), 88-94.

Hassan, A., & Bach, C. (2014, April). WiMAX Basics From Deployments to PHY Improvements. ASEE.

Nair, G. P. (2013). Nano core-A Review on 5G Mobile Communications. International Journal of Computer Science and Mobile Computing, ICMIC13, 124-133.

Rault, T., Bouabdallah, A., & Challal, Y. (2014). Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks, 67, 104-122.

Shaikh, F. K., & Zeadally, S. (2016). Energy harvesting in wireless sensor networks: A comprehensive review. Renewable and Sustainable Energy Reviews, 55, 1041-1054.

Sulyman, A. I., Nassar, A. T., Samimi, M. K., Maccartney, G. R., Rappaport, T. S., & Alsanie, A. (2014). Radio propagation path loss models for 5G cellular networks in the 28 GHz and 38 GHz millimeter-wave bands. IEEE Communications Magazine, 52(9), 78-86.

Tsampasis, E., Bargiotas, D., Elias, C., & Sarakis, L. (2016, January). Communication challenges in Smart Grid. In MATEC Web of Conferences (Vol. 41). EDP Sciences.

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.

Usman, A., & Shami, S. H. (2013). Evolution of communication technologies for smart grid applications. Renewable and Sustainable Energy Reviews, 19, 191-199.

Zhang, L., Afanasyev, A., Burke, J., Jacobson, V., Crowley, P., Papadopoulos, C., ... & Zhang, B. (2014). Named data networking. ACM SIGCOMM Computer Communication Review, 44(3), 66-73.

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