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Mobility in healthcare helps to promote clinical collaboration. By providing timely access to Patient Health Information, it helps doctors to take critical care decisions. Mobility in healthcare is enhancing the accessibility of critical firm and clinical systems. These days, condition devices are advancing closer to patient�s point-of-care. Network based mobility protocols are suitable for 6LoWPAN because in these protocols network initiates the message signaling and reduces the load on low power sensor nodes by relieving them from participating in mobility procedure, result in enhancing lifetime of network. Proxy Mobile IPv6 (PMIPv6) is suitable mobility solution as it is Network based mobility protocol alongside it provides single hop communication but single hop communication is not sufficient for LoWPAN. Sensor Proxy Mobile IPv6 (SPMIPv6) is an optimization of PMIPv6 and appropriate for low power sensor nodes as it reduces message signaling overload ,optimize power consumption and minimize mobility cost compare to PMIPv6 and MIPv6.

Wireless sensor networks (WSN), Mobility Support, and MIPV6

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[3] M. S. Shahamabadi, B. M. Ali, N. K. Noordin, M. F. B. A. Rasid, P. Varahram, and A. J. Jara, �A NEMO-HWSN solution to support 6LoWPAN network mobility in hospital wireless sensor network,� Comput. Sci. Inf. Syst., vol. 11, no. 3, pp. 943�960, 2014.
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[9] D. Gurjar, I. Alam, P. B. B. Tiwari, and P. G. N. Pandey, �Wireless Sensor Network : an emerging entrant in Healthcare Wireless Sensor Network : an emerging entrant in Healthcare,� no. June, 2016.
[10] M. Bouaziz and A. Rachedi, �A survey on mobility management protocols in Wireless Sensor Networks based on 6LoWPAN technology To cite this version : A Survey on Mobility Management Protocols in Wireless Sensor Networks based on 6LoWPAN Technology,� 2015.
[11] S. Singh, �Security For Wireless Sensor Network,� vol. 3, no. 6, pp. 2393�2399, 2011.
[12] R. A. Khan and C. Engineering, �Performance Analysis of Host Based and Network Based IP Mobility Management Schemes,� vol. 6, pp. 1798�1803, 2008.
[13] J. Pieterse, R. Wolhuter, and N. Mitton, �Implementation and analysis of FMIPv6, an enhancement of MIPv6,� Lect. Notes Inst. Comput. Sci. Soc. Telecommun. Eng. LNICST, vol. 111, pp. 351�364, 2013.
[14] F. T. Zohra, S. Azam, and M. Rahman, �Overview of IPv6 Mobility Management Protocols and their Handover Performances,� no. 3, 2014.
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[16] S. Salehian and R. Shamshiri, �A Survey on Mobility Management Protocols in Wireless Sensor Network-internet Protocol,� Indian J. Sci. Technol., vol. 8, no. 52998, pp. 974�6846, 2015.
[17] M. H. Habaebi, �Macro/micro-mobility fast handover in hierarchical mobile IPv6,� Comput. Commun., vol. 29, no. 5, pp. 611�617, 2006.
[18] J. Kim, R. Haw, S. Member, and E. J. Cho, �A 6LoWPAN Sensor Node Mobility Scheme Based on Proxy Mobile IPv6,� vol. 11, no. 12, pp. 2060�2072, 2012.
[19] M. M. Islam and E. N. Huh, �Sensor proxy mobile IPv6 (SPMIPv6)-a novel scheme for mobility supported IP-WSNs,� Sensors, vol. 11, no. 2, pp. 1865�1887, 2011.
[20] M. Ha, D. Kim, S. H. Kim, and S. Hong, �Inter-MARIO: A fast and seamless mobility protocol to support inter-PAN handover in 6LoWPAN,� GLOBECOM - IEEE Glob. Telecommun. Conf., pp. 1�6, 2010.

R. Narang, A. Malik, "Mobility support in Wireless Sensor Network in Healthcare-A Survey," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.60-65, 2017.

Clustering is the process of organizing objects into groups whose members are similar in some way and is very important technique in data mining as it has its applications spread extensively, e.g. marketing, biology, pattern recognition etc. So summarize the data stream in the real life with the online process is called as micro-cluster but it shows the density when we are combining the data in the one place. In the offline process we are using the modification clustering algorithm to re-clustering into larger cluster. For that the center of micro-cluster point as the pseudo point with density randomly calculates their weight. That density information area of micro-cluster is not preserved the online process. So used DBSTREAM, the first micro-cluster based on online clustering component capture the density between micro-cluster via shared density graph. We develop and evaluate a new method to address this problem for micro-cluster-based algorithms. The density information in this graph is then exploited for re-clustering based on actual density between adjacent micro-clusters. For that shared density graph improves clustering quality over other popular data stream clustering methods which require the creation of a larger number of smaller micro-clusters to achieve comparable results.

Data mining, data stream clustering, density-based clustering

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[14]. Enakshmi Nandi1, Debabrata Sarddar �A Modified MapReduce-K-Means Clustering Based Load Distribution Method for Wireless Sensor Network in Mobile Cloud computing� ,2016
[15]. Pritika goel, �An Improved Load Balancing Technique in Weighted Clustering Algorithm� ,2016.Available: http://www.ijcseonline.org/pdf_paper_view.php?paper_id=972&18-IJCSE-01678.pdf

P.V. Desai, V.S. Gaikawad, "Novel approach for data stream clustering through micro-clusters shared Density," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.66-69, 2017.

Interlinking of IOT, Big Data and Android, Now arises a question, what�s link between these technologies? As, IoT is a technology where world is stepping towards future development, Internet of Things (IOT), Internet is interconnecting of networks, Things means Devices or Objects (Interaction between Objects),IOT is not mainly creating smart gadgets or connecting more things to the internet, machine-to-machine(M2M) technologies can be seen as the first phase, In the next phase the connectivity of physical objects together connected in support of intelligent decision making operating with Sensors and Actuators. A sensor is used for grasping the input from any object and an Actuator is used for activating the device based on the input taken from a sensor, here comes the need of Big data Analytics, Data was getting seriously big even before IOT entered the picture. If Big data is �Heart� of advancement, IoT is the �Soul�. Where sensors sense objects continuously time to time and forward in every bit of second for processing which in cause memory load that should be maintained, so the huge amounts of data should be collected and maintenance with Big data and Data Analytics for extracting actual information from huge amounts of data. Now comes Smart App which has more scope with introducing of smart gadgets where maximum people are aware the applications in them. So for user interaction purpose we introduce mobile apps by directly giving access to the users. In this paper I have given brief introduction of Interlinking of IoT, Big Data and Smart mobiles focusing on one major problem in society, Garbage Monitoring replacing with Smart Garbage Monitoring.

IoT, Big Data, Android, Sensor, Actuator, Smart Gadgets, Data Analytics

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R. Gorli , "Interlinking OF IoT, Big data, Smart Mobile app with Smart Garbage Monitoring," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.70-74, 2017.

Recently, extreme demand of mobile communication, small cells in millimeter wave bands within macro-cell network is attracting the attention in academics as well as the industries. Evolution of 4G is essential in keeping up with the exponential growth of mobile data network traffic. Up to 7GHz bandwidth has been allocated worldwide for license-free 60GHz radio frequency. Multiple giga-bites per second can be transmitted by utilizing the huge unlicensed bandwidth using mmWave communication in the 60GHz band. Numerous amount of spectrum available in micro frequencies are able to provide cost effective communication between the nodes in small cell via high capacity backhaul. Wireless backhaul is an attractive option for small cells as it provides a less expensive and easy-to-deploy over fiber. However, there are multitude of bands and features (e.g. LOS/NLOS, spatial multiplexing etc.) connected to wireless backhaul that need to be used smartly for small cells. Candidate bands include: sub-6 GHz band that is useful in non-line-of-sight (NLOS) scenarios, microwave band (6�42 GHz) that is used in point-to-point line-of-sight (LOS) scenarios, and mmWave bands (e.g. 60, 70 and 80 GHz) that are recently being commercially used in LOS scenarios. In many deployment topologies, it is more beneficial to use aggregator nodes, located at the roof tops of tall buildings near small cells. The protocol supports concurrent transmission in minimum frequency to the greater extent. Further to enhance the efficiency of network, performance analysis and different parameters will be calculated.

Device-to-Device communication (D2D), Heterogeneous cellular network, millimeter wave, MAC scheduling, spatial re-use

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H.K. Dandage, V.S. Gaikwad, "Device-to-Device Communication in Wireless Network using mmWave within Small Cells and Exploiting Spatial Reuse," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.75-79, 2017.

Video download and sharing is one of the most popular applications in the field of mobile computing. Reducing the energy consumption of the mobile devices is a major challenge in sustaining multimedia applications. In this work, an adaptive framework called V-Share is developed for group of users with common interest to collaboratively download a video file from the cloud and share it among them. In V-Share, each node downloads only a segment of video file and the downloaded segments are reassembled and merged into a complete file by the coordinator node and then it is shared to all users of the ad-hoc group. Only the mobile nodes with relatively good battery level participate in download process whereas the nodes with low battery level remain futile. This greatly reduces the battery consumption of the mobile devices. Seamless connectivity is established between the mobile devices and the cloud using 3G and WiFi links enable cooperation among smart phones to smoothen the service.

Ad hoc cloud; Seamless connectivity; File sharing; Energy saving, Collaborative download

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[7] P.Sangeetha and Dr.R.Mala, "Cross-Layer arrangement for Wireless Mesh Networks", International Journal of Computer Sciences and Engineering, Volume-02, Issue-09, Page No (85-89), Sep -2014

G. Santhi, "V-Share: An Energy Efficient Collaborative Video Download and Sharing Application using Ad-hoc Cloud," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.80-84, 2017.

This paper presents an automatic method for the segmentation of Glioblastoma multiforme(GBM) tumors from MRI images. The global search ability of Genetic Algorithm (GA) to optimize the Fuzzy C-means (FCM) clustering algorithm to obtain better clustering center. But the prematurity problem of GA itself has bad effects on the whole clustering. Therefore, in order to optimize the traditional GA-FCM algorithm�s clustering effect, in this work, we introduce the Opposition-based learning mechanism into GA, to construct an OBL-Genetic Algorithm (OBL-GA). The improved algorithm forms the next generation of evolutionary population by selecting the superior individuals in the collection of the sub generation and reverse sub generation, to increase the population diversity, and final to overcome the prematurity problem of GA. Then applying the improved algorithm to FCM, which gives better results and then resultant image, is applied with level sets, to exact delineation of GBM tumor. The validation is performed on a labeled BRATS data set. Our segmentation results are highly accurate, and compare favorably to the state of the art.

Fuzzy-c means,Glioblastoma multiforme,Segmentation,Genetic Algorithm,Opposition based learning,MRI

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B.S. Rao, E.S. Reddy, "OBL-GA based FCM with level sets for automatic GBM tumor segmentation in MR Images," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.85-20, 2017.

Cloud computing is a web technology computing which requires large scale processing and computing. For this extensive processing, it requires security and protection in cloud computing for shareable configurable resources for on-demand access. This paper describes about the cloud computing merits and demerits of existing security and protection models in cloud computing

indexing, private cloud,protected cloud, public cloud, service provider, client owner

[1] A. K. Singh, �A Study on Merits and Demerits of SAN Protocols,� vol. 3, no. X, pp. 1�5, 2015.
[2] X. Qiu, Y. Dai, Y. Xiang, L. Xing, and S. Member, �Reliability, Performance , and Power Consumption of a Cloud Service,� vol. 46, no. 3
[3] Surabhi Shukla and Dharamjeet kumar, "Cloud�s Software- Security as a Service(S-SaaS) via Biometrics", International Journal of Computer Sciences and Engineering, Volume-02, Issue-03, Page No (119-124), Mar -2014
[4] W. Li, Y. Yang, and D. Yuan, �Ensuring Cloud Data Reliability with Minimum Replication by Proactive Replica Checking,� IEEE Trans. Comput., vol. 65, no. 5
[5] M. Kangas, S. Glisic, S. Member, Y. Fang, and P. Li, �Resource Harvesting in Cognitive Wireless Computing Networks With Mobile Clouds and Virtualized Distributed Data Centers : Performance Limits,� IEEE Trans. Cogn. Commun. Netw., vol. 1, no. 3
[6] Richa Arya , "Triple Security of File System for Cloud Computing", International Journal of Computer Sciences and Engineering, Volume-02, Issue-03, Page No (148-154), Mar -2014
[7] G. Fan, H. Yu, S. Member, and L. Chen, �A Formal Aspect-Oriented Method for Modeling and Analyzing Adaptive Resource Scheduling in Cloud Computing,� vol. 13, no. 2, p.
[8] Shaheen Ayyub and Devshree Roy, "Cloud Computing Characteristics and Security Issues", International Journal of Computer Sciences and Engineering, Volume-01, Issue-04, Page No (18-22), Dec -2013.
[9] J. Bacon, D. Eyers, T. F. J.-M. Pasquier, J. Singh, I. Papagiannis, and P. Pietzuch, �Information Flow Control for Secure Cloud Computing,� IEEE Trans. Netw. Serv. Manag., vol. 11, no. 1,
[10] M. Amoon, �Adaptive Framework for Reliable Cloud Computing Environment,� IEEE Access, vol. 3536, no. c
[11] K. Goyal, �International Journal of Advanced Research in Computer Science and Software Engineering Review of Different Energy Saving Techniques in Cloud Computing,� vol. 3, no. 7, pp. 1038�1042, 2013.
[12] A. Sharma, S. Gupta, D. Mann, and S. Akhtar, �A Combined Model to Ensure Complete Security and Reliability in Cloud Computing,� vol. I, pp. 21�24, 2015.

N.K. Singh, A.K. Singh, "A Study on Virtue and Faults of Security in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.93-94, 2017.

Cloud computing provides on-demand access to distributed resources on paid basis. Everybody wants to use these services to reduce the cost of infrastructure and maintenance, therefore the load on cloud is increasing day by day. Balancing the load is one of the most important issue that cloud computing is facing today. The load should be distributed fairly among all the nodes. Proper load balancing can reduce the energy consumption and carbon emission. This will helps to achieve Green Computing. There are many algorithms for load balancing. All these algorithms work in different ways and have some advantages and limitations. The most important for load balancing algorithms is to consider the characteristics like fairness, throughput, fault tolerance, overhead, performance, and response time and resource utilization. This paper mainly focuses on the concept of load balancing, literature survey on load balancing techniques and different measurement parameters.

Cloud Computing; Load Balancing; Static Algorithms; Dynamic Algorithms;Hierarchical Load Balancing

[1] Peter Mell Timothy Grance�, The NIST Definition of Cloud Computing�, National Institute of Standards and Technology Special Publication 800-145(September 2011),csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf
[2] Rajwinder Kaur and Pawan Luthra,� Load Balancing in Cloud Computing�, Association of Computer Electronics and Electrical Engineers, 2014, DOI: 02.ITC.2014.5.92
[3] Ashalatha R; J. Agarkhed, �Dynamic load balancing methods for resource optimization in cloud computing environment �, 2015 Annual IEEE India Conference (INDICON) , Pages: 1 - 6, DOI: 10.1109/INDICON.2015.7443148
[4] Garima Rastogi, Dr Rama Sushil, �Analytical Literature Survey on Existing Load Balancing Schemes in Cloud Computing�, 2015 International Conference on Green Computing and Internet of Things (ICGCloT), pages:1506-1510
[5] R. Kanakala; V. K. Reddy; K. Karthik, " Performance analysis of load balancing techniques in cloud computing environment�, 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), Pages: 1 - 6, DOI: 10.1109/ICECCT.2015.7226052
[6] K. Garala; N. Goswami; P. D. Maheta, " A performance analysis of load Balancing algorithms in Cloud environment �, 2015 International conference on Computer Communication and Informatics (ICCCI), Pages: 1 - 6, DOI: 10.1109/ICCCI.2015.7218063
[7] A.N. Ivanisenko; T. A. Radivilova , �Survey of major load balancing algorithms in distributed system �, Information Technologies in Innovation Business Conference (ITIB), 2015 ,Pages: 89 - 92, DOI: 10.1109/ITIB.2015.7355061
[8] Sidra Aslam, Munam Ali Shah, �Load Balancing Algorithms in Cloud Computing: A Survey of Modern Techniques�, 2015 National Software Engineering Conference (NSEC 2015)
[9] A. A. Jaiswal, Dr. Sanjeev Jain,� An Approach towards the Dynamic Load Management Techniques in Cloud Computing Environment�, 2014 International Conference on Power, Automation and Communication (INPAC)
[10] G.Punetha Sarmila,Dr.N.Gnanambigai, Dr.P.Dinadayalan,� Survey on Fault Tolerant �Load Balancing Algorithms in Cloud Computing�, IEEE Sponsored 2nd International Conference On Electronics And Communication System (ICECS 2015), Pages-1715-1720
[11] Surbhi Kapoor, Dr. Chetna Dabas,� Cluster Based Load Balancing in Cloud Computing�, 2015 Eighth International Conference on Contemporary Computing (IC3)
[12] Shridhar G.Domanal and G.Ram Mohana Reddy, � Load Balancing in Cloud Computing Using Modified Throttled Algorithm �, 2013 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)
[13] Aarti Vig, Rajendra Singh Kushwah and Shivpratap Singh Kushwah, �An Efficient distributed Approach for Load Balancing in Cloud Computing�, 2015 International Conference on Computational Intelligence and Communication Networks

R.S Sajjan, R.Y. Biradar, "Load Balancing and its Algorithms in Cloud Computing: A Survey," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.95-100, 2017.

CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is a method which is used to identify whether user is robot or human. For security concern it is required to know by using some kind of Turing Test. Traditionally, distorted letters in non-uniform positions are generally used for this test, because it has been considered that, it is easy to analyze the distorted letters by human which cannot by robot or bots. But later it could also be recognized by robot, then various research has been made, based on 3d alphanumeric letters, numerical calculations, moving alphanumeric letters, OTP & gaming. But some time distorted letters, 3d letters & moving alphabets are also difficult to recognize by human, it becomes irritating. And numerical calculation is often become easy now by robot, based on neural networks & OTP[4] takes longer time because it is depend on mobile network, so that is why these techniques are also not convenient for human. It should be very easy for human and almost impossible by robots. Then a new promising way was introduced i.e. gaming based CAPTCHA, it is most attractive and cognitive way in the world of CAPTCHA. This is the most recent method used by various personals. But the game which is used for is static, it means you will have to drag & drop static object to the given static target which may be breakable by some intelligent systems. So, that is why here it is the solution which proposes a dynamic object & target gaming based CAPTCHA, it means that here the target is not static as well as object, you will have to drag & drop moving object to moving target which is considered as impossible for robot in given time, because we are also using a CAPTCHA session, you will get 10-15 seconds to achieve your goal and it can be achieved by 5 to 8 seconds by human or may be less. But not possible by robot because after given session time another CAPTCHA will be appeared to achieve. So this technique is based on totally dynamic features and sessions which is very easy for human but almost impossible by robots. This is the newest way in the world of gaming CAPTCHA. Here a little survey has been made on existing systems.

CAPTCHA, Drag and Drop, 3-D Alphabets etc

[1] Jing Song Cui, Li Jing Wang, Jing Ting Mei, Da Zhang, Xia Wang, Yang Peng, Wu Zhou Zhang in IEEE 2009, �CAPTCHA Design Based on Moving Object Recognition Problem.�
[2] Jing-Song Cui, Jing-Ting Mei, Xia Wang, Da Zhang, Wu-Zhou Zhang, �A CAPTCHA Implementation Based on 3D Animation� 2009 International Conference on Multimedia Information Networking and Security of IEEE.
[3] Ibrahim Furkan Ince, Yucel Batu Salman, Mustafa ErenYildirim and Tae-Cheon Yang , �Execution time prediction for 3d interactive captcha by keystroke level model�, 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology of IEEE.
[4] P.Arthy and J.Revathi, "Against Spyware by Captcha in Graphical Pin Arrangement", International Journal of Computer Sciences and Engineering, Volume-03, Issue-01, Page No (165-172), Jan -2015
[5] Yang-Wai Chow1, Willy Susilo2, Hua-Yu Zhou1, �CAPTCHA Challenges for Massively Multiplayer Online Games�, 2010 International Conference on Cyberworlds of IEEE.
[6] Aadhirai R, Sathish Kumar P J and Vishnupriya S , �Image CAPTCHA: Based on Human Understanding of Real World Distances �, IEEE Proceedings of 4th International Conference on Intelligent Human Computer Interaction, Kharagpur, India, December 27-29, 2012.
[7] Song Gao, Manar Mohamed, NiteshSaxena and Chengcui Zhang , �Gaming the game: Defeating a game CAPTCHA with efficient and robust hybrid attacks� , IEEE 2014.
[8] Seyed Mohammad Reza SaadatBeheshti, PanosLiatsis , �How Humans Can Help Computers to Solve an Artificial Problem� ,international conference IEEE ,2015.
[9] Artem Shumilov, Andrey Philippovich , �Cloud-Based CAPTCHA Service�.
[10] Luis von Ahn, Manuel Blum, Nicholas J Hopper and John Lanford, � CAPTCHA : Using Hard AI Problems for Security�,Carnegie Mellon University.

V. Kumar, A. Barve, "A Survey on Existing CAPTCHA Techniques and Proposed Gaming CAPTCHA for Better Security Analysis," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.101-106, 2017.

A smart grid is an electrical grid linking electricity production, consumption and storage and coordinating them autonomously. This type of network therefore makes it possible to switch from a demand-driven production system to a supply-based consumption system, which will have to adapt in future to the random variations of the production of wind and solar energies. Combined with other technologies such as pumped storage or gas combined cycle facilities, particularly flexible, this network must contribute to improving security of supply, reducing costs related to the distribution network and the to integrate renewable energies into the grid and to improve the efficiency of the entire system. A smart grid combines the existing electricity grid with information and communication technology applications. However, if several current technologies can already be used, they must first be tested in the form of individual components, since the technical implementation depends on the stability and effectiveness of their interaction. Indeed, except in some research projects, no smart grid ensures a fully automated control consumer devices and production facilities exist in the world: it is still a concept. The current tests on smart meters, already deployed on a large scale in some countries, are a first step in the implementation of these smart grids. This technology should encourage final users to save electricity and encourage decentralized injection control. However, their introduction in Switzerland is hampered by data protection issues, lack of standards in this field and a lack of clarity in the allocation of roles and costs. The success of smart grids will depend in large part on the economic interests of the various stakeholders. Once this happens, the likelihood of a change in our existing grid in smart grid will also emerge.

Smart Grid, Renewable Energy, Energy Transition, Innovation, Energy Consumption

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[2] Yuvaraj S. Patil, Dr. Mrs. Swati V. Sankpal,�� A Survey on Cyber Security for Smart Grid Networks��, International Journal on Recent and Innovation Trends in Computing and Communication, IJRITCC | May 2015.Page No(2503-2507) .
[3] Hemant Joshi, Vivek Pandya,�� Development of Smart Plug and Energy Price Forecasting
Technique to Reduce Peak Demand and Cost of Energy in Smart Grid��, International Journal of Innovative Research in Advanced Engineering (IJIRAE), Issue 12, Volume 2 (December 2015).Page No(90-99).
[4] Mario FAschang, Mark Stefan, Friederich Kupzog, Alfred Einfalt, Stephan Cejka,�� A Flexible And Performant Framework Hosting Smart Grid Applications��, Cired Workshop - Helsinki 14-15 June 2016.Paper 0255,Page No(1-4).
[5] Vinay Kumar K and Balakrishna R,�� Smart Grid: Advanced Metering Infrastructure (AMI) & Distribution Management Systems (DMS)��, International Journal of Computer Sciences and Engineering,IJCSE, Vol.-3(11), PP(19-22) Nov 2015, E-ISSN: 2347-2693
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[8] Palak Kalra,�� Theft Detection Schemes For Smart Grid Application��, International Journal Of Electrical Engineering & Technology (Ijeet), Volume 5, Issue 12, December (2014), Page No (321-327).
[9] Jaimala Gambhir,�� An Overview Of Smart GRID��, International Journal of Engineering Inventions ISSN: 2278-7461, www.ijeijournal.com Volume 1, Issue 7(October2012) Page No( 90-99).
[10]SMART Grids Laboratories Inventory 2015, ISSN 1018-5593 (print) doi: 10.2790/451423 (online), Luxembourg: Publications Office of the European Union, 2015 , European Union, 2015,Page No (1-93).
[11] Rucha Vilasrao Deshmukh, Sunita A Upasani,�� Future Scope in Smart Grid��, ISSN: 2455-2631, May 2016 IJSDR | Volume 1, Issue 5,Page No(540-542).
[12] P.Vijayapriya, Garauv Bapna, Dr.D.P.Kothari,�� Smart Tariff for Smart Meters In Smart Grid��, P.Vijayapriya et al. / International Journal of Engineering and Technology Vol.2 (5), 2010, 310-315, ISSN : 0975-4024,Page No( 310-315).
[13] Viren Patel, Prof. Mithila S. Zodape,�� Implementation of Smart Grid System using Digital Energy Meter��, International Journal of Advance Engineering and Research Development, Volume 2,Issue 5, May -2015, IJAERD-2015,PageNo(1533-1537).
[14] Archana S. Talhar (Belge), Sanjay B. Bodkhe,�� MODERNIZATION OF TRADITIONAL GRID INTO SMART GRID THROUGH RENEWABLE SOURCES��, ISSN 0976 � 6545(Print),ISSN 0976 � 6553(Online),Volume 5, Issue 2, February (2014), Page No(1-11).
[15]U. Suganya, C.Subhalakshmipriya,�� Smart-Grid In Electrical And Electronical Communication Technology��, International Journal of Engineering Research and General Science Volume 3, Issue 1, January-February, 2015 ISSN 2091-2730,Page No(386-393).
[16] S Priyadharshini , Dr.B.Meenakshi,�� Reduction of Energy Storage Requirements in Future Smart Grid Using Electric Springs��, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 3, Special Issue 1, February 2014,Page No(201-205).
[17] Anil K Jain, Toshi Mandloi,�� Integration of Renewable Energy Sources in Smart Grid Systems, and their constraints��, International Journal of Modern Trends in Engineering and Research, IJMTER-2015,Page No(429- 434).
[18] Gueddouch Touria and Saad Abdallah, "Modeling of a Building With The Aim of The Evaluation of its Energy Consumption Application to a Typical Building in Morocco", International Journal of Computer Sciences and Engineering, Volume-02, Issue-02, Page No (1-5), Feb -2014, E-ISSN: 2347-2693.
[19] Raksha Kala,�� Energy Conservation and Monitoring System for Smart City using Internet of Things��, SSRG International Journal of Computer Science and Engin eering (SSRG-IJCSE) � volume 3 Issue 8�August 2016,Page No(20-24).
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[21] Soumya Mukherjee, Sougata Jana, Amartya Roy, Swapan Santra,�� Hybrid Power Generation Model using Wind Energy and Solar Energy��, International Journal of Computer Sciences and Engineering, Vol.-4(6), Aug 2016, E-ISSN: 2347-2693,Page No(60-64).
[22] Tayeb Amegroud,�� Morocco�s Power Sector Transition: Achievements and Potential��, ISSN 2280-4341 | ISBN 978-88-98650-29-3, 2015 IAIIAI Working papers 15 | 05 - February 2015.Page No(1-21).
[23] Mohamed Oukili , Smail Zouggar , Mohamed Seddik , Taoufik Ouchbel , Fran�ois Vall�e , Mohamed El Hafiani,�� Comparative Study of the Moroccan Power Grid Reliability in Presence of Photovoltaic and Wind Generation��, Smart Grid and Renewable Energy, 2013, 4, 366-377 http://dx.doi.org/10.4236/sgre.2013.44043 Published Online July 2013 .
[24] Vinay Kumar K and Dr. Balakrishna R, "Smart Grid: Advanced Metering Infrastructure (AMI) & Distribution Management Systems (DMS)", International Journal of Computer Sciences and Engineering (IJCSE), Volume-03, Issue-11, Page No (19-22), Nov -2015, E-ISSN: 2347-2693

S. Riahi, Y. Riahi, "Renewable Energies in MOROCCO: Situation of the Sector, Development Potential of the Sector," International Journal of Computer Sciences and Engineering, Vol.5, Issue.1, pp.107-114, 2017.