The growth of Internet and other web technologies requires the development of new algorithms and architectures for parallel and distributed computing. International journal of Distributed and parallel systems is a bi monthly open access peer-reviewed journal aims to publish high quality scientific papers arising from original research and development from the international community in the areas of parallel and distributed systems. IJDPS serves as a platform for engineers and researchers to present new ideas and system technology, with an interactive and friendly, but strongly professional atmosphere.

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International Journal of Distributed and Parallel
systems (IJDPS)
ISSN : 0976 - 9757 [Online] ; 2229 - 3957 [Print]
http://airccse.org/journal/ijdps/ijdps.html

2. REAL-TIME ADAPTIVE ENERGY-SCHEDULING
ALGORITHM FOR VIRTUALIZED CLOUD COMPUTING
D B Srinivas1
, H K Krishnappa2
, Rajan M A3
, Sujay N. Hegde4
1,4
Nitte Meenakshi Institute of Technology, Bangalore, India, 2
R V College of Engineering,
Bangalore, India, 3
TCS Research and Innovation, Bangalore, India
ABSTRACT
Cloud computing becomes an ideal computing paradigm for scientific and commercial
applications. The increased availability of the cloud models and allied developing models creates
easier computing cloud environment. Energy consumption and effective energy management are
the two important challenges in virtualized computing platforms. Energy consumption can be
minimized by allocating computationally intensive tasks to a resource at a suitable frequency. An
optimal Dynamic Voltage and Frequency Scaling (DVFS) based strategy of task allocation can
minimize the overall consumption of energy and meet the required QoS. However, they do not
control the internal and external switching to server frequencies, which causes the degradation of
performance. In this paper, we propose the Real Time Adaptive EnergyScheduling (RTAES)
algorithm by manipulating the reconfiguring proficiency of Cloud ComputingVirtualized Data
Centers (CCVDCs) for computationally intensive applications. The RTAES algorithm minimizes
consumption of energy and time during computation, reconfiguration and communication. Our
proposed model confirms the effectiveness of its implementation, scalability, power consumption
and execution time with respect to other existing approaches.
KEYWORDS
Virtual Machine (VM); Virtualized Data Centers (VDCs); Quality of Service (QoS); Dynamic
Voltage and Frequency Scaling (DVFS); Real Time Adaptive Energy-Scheduling (RTAES).
For More Details : http://aircconline.com/ijdps/V10N1/10119ijdps01.pdf
Volume Link : http://airccse.org/journal/ijdps/current2019.html

3. REFERENCES
[1] Lizhe Wang, Gregor von Laszewski, Jai Dayal, Thomas R. Furlani, Thermal aware workload
scheduling with backfilling for green data centers, in: IPCCC, 2009, pp. 289–296.
[2] William Forrest, How to cut data centre carbon emissions? Website, December 2008.
[3] Yongpan Liu et al. “Thermal vs energy optimization for dvfs-enabled processors in
embedded systems”. In: Quality Electronic Design, 2007. ISQED’07. 8th International
Symposium on. IEEE. 2007, pp. 204–209.
[4] J.-J. Chen and C.-F. Kuo, ``Energy-efficient scheduling for real-time systems on dynamic
voltage scaling (DVS) platforms,'' in Proc. IEEE RTCSA, Aug. 2007, pp. 28-38.
[5] V. Devadas and H. Aydin, ``Coordinated power management of periodic real-time tasks on
chip multiprocessors,'' in Proc. Green Comput. Conf., 2010, pp. 61-72.
[6] Arabnejad, H., Barbosa, J.G.: A budget constrained scheduling algorithm for workflow
applications. J. Grid Comput. 12(4), 15 (2014)
[7] Durillo, J.J., Prodan, R.: Multi-objective workflow scheduling in amazon ec2. Cluster
Comput. 17(2), 169–189 (2014)
[8] Q. Wu, F. Ishikawa, Q. Zhu, Y. Xia and J. Wen, "Deadline-Constrained Cost Optimization
Approaches for Workflow Scheduling in Clouds," in IEEE Transactions on Parallel and
Distributed Systems, vol. 28, no. 12, pp. 3401-3412, Dec. 2017.
[9] S. Chinprasertsuk and S. Gertphol, "Power model for virtual machine in cloud computing,"
2014 11th
International Joint Conference on Computer Science and Software Engineering
(JCSSE), Chon Buri, 2014, pp. 140-145.
[10] T. AlEnawy et al., ``Energy-aware task allocation for rate monotonic scheduling,'' in Proc.
IEEE RTAS, Apr. 2005, pp. 213-223.
[11] C.-Y. Yang, J.-J. Chen, T.-W. Kuo, and L. Thiele, ``An approximation scheme for energy-
efficient scheduling of real-time tasks in heterogeneous multiprocessor systems,'' in Proc. DATE,
2009, pp.694-699.
[12] E. Seo, J. Jeong, S. Park, and J. Lee, ``Energy efcient scheduling of realtime tasks on
multicore processors,'' IEEE Trans. Parallel Distrib. Syst., vol. 19, no. 11, pp. 1540-1552, Nov.
2008.
[13] C. Xian and Y.-H. Lu, ``Dynamic voltage scaling for multitasking real-time systems with
uncertain execution time,'' in Proc. ACM GLSVLSI, 2006, pp. 392-397.

4. [14] C. Xian, Y.-H. Lu, and Z. Li, ``Energy-aware scheduling for real-time multiprocessor
systems with uncertain task execution time,'' in Proc. ACM DAC, 2007, pp. 664-669.
[15] Baliga, J, Ayre, R. W., Hinton, K., and Tucker, R. 2011. Green cloud computing: Balancing
energy in processing, storage, and transport. Proceedings of the IEEE, 2011. 99(1):149–167.
[16] Canali, C. and Lancellotti, R. Parameter Tuning for Scalable Multi-Resource Server
Consolidation in Cloud Systems. Communications Software and Systems, 2016.
[17] Urgaonkar, R., Kozat, U. C., Igarashi, K., and Neely, M. J. Dynamic resource allocation and
power management in virtualized data centers. In NOMS, 2010, pp 479–486. IEEE.
[18] A. Alsarhan, A. Itradat, A. Y. Al-Dubai, A. Y. Zomaya and G. Min, "Adaptive Resource
Allocation and Provisioning in Multi-Service Cloud Environments," in IEEE Transactions on
Parallel and Distributed Systems, vol. 29, no. 1, pp. 31-42, Jan. 1 2018.
[19] P. Arroba, J. M. Moya, J. L. Ayala and R. Buyya, "DVFS-Aware Consolidation for Energy-
Efficient Clouds," 2015 International Conference on Parallel Architecture and Compilation
(PACT), San Francisco, CA, 2015, pp. 494-495.
[20] W. Chawarut and L. Woraphon, "Energy-aware and real-time service management in cloud
computing," 2013 10th International Conference on Electrical Engineering/Electronics,
Computer, Telecommunications and Information Technology, Krabi, 2013, pp. 1-5.
[21] H. Faragardi, A. Rajabi, K. Sandström and T. Nolte, "EAICA: An energy-aware resource
provisioning algorithm for Real-Time Cloud services," 2016 IEEE 21st International Conference
on Emerging Technologies and Factory Automation (ETFA), Berlin, 2016, pp.1-10.
[22] Z. Bagheri and K. Zamanifar, "Enhancing energy efficiency in resource allocation for real-
time cloud services," Telecommunications (IST), 2014 7th International Symposium on, Tehran,
2014, pp. 701-706.
[23] Zheng, W., Sakellariou, R.: Budget-deadline constrained workflow planning for admission
control. J. Grid Comput. 11(4), 105–119, 2013.
[24] T. Knauth and C. Fetzer, “Energy-aware scheduling for infrastructure clouds,” in Cloud
Computing Technology and Science (CloudCom), 2012,IEEE 4th International Conference on.
IEEE, 2012, pp.58–65.
[25] S. K. Garg, C. S. Yeo, and R. Buyya, “Green cloud framework for improving carbon
efficiency of clouds,” in Euro-Par 2011 Parallel Processing. Springer, 2011, pp. 491–502.
[26] Z. Zhu, G. Zhang, M. Li and X. Liu, "Evolutionary Multi-Objective Workflow Scheduling
in Cloud," in IEEE Transactions on Parallel and Distributed Systems, vol. 27, no. 5, pp. 1344-
1357, May 1 2016.

5. [27] D.B Srinivas, Puneeth R.P, Rajan M.A, Sanjay. H.A, An integrated framework to measure
the energy consumption of a parallel application on a computational grid, International Journal of
Computer Science and Network Security, VOL.16 No.7, pp. 94-98, 2016.

6. ADVANCED DIFFUSION APPROACH TO DYNAMIC
LOAD-BALANCING FOR CLOUD STORAGE
Eman Daraghmi1
and Yousef-Awwad Daraghmi2
1
Department of Applied Computing, Palestine Technical University Kadoori (PTUK),
Tulkarm, Palestine
2
Department of Computer Systems Engineering, Palestine Technical University Kadoori
(PTUK), Tulkarm, Palestine
ABSTRACT
Load-balancing techniques have become a critical function in cloud storage systems that consist
of complex heterogeneous networks of nodes with different capacities. However, the
convergence rate of any load-balancing algorithm as well as its performance deteriorated as the
number of nodes in the system, the diameter of the network and the communication overhead
increased. Therefore, this paper presents an approach aims at scaling the system out not up - in
other words, allowing the system to be expanded by adding more nodes without the need to
increase the power of each node while at the same time increasing the overall performance of the
system. Also, our proposal aims at improving the performance by not only considering the
parameters that will affect the algorithm performance but also simplifying the structure of the
network that will execute the algorithm. Our proposal was evaluated through mathematical
analysis as well as computer simulations, and it was compared with the centralized approach and
the original diffusion technique. Results show that our solution outperforms them in terms of
throughput and response time. Finally, we proved that our proposal converges to the state of
equilibrium where the loads in all in-domain nodes are the same since each node receives an
amount of load proportional to its capacity. Therefore, we conclude that this approach would
have an advantage of being fair, simple and no node is privileged.
KEYWORDS
Load balancing, cloud storage, Heterogeneous, Simulation, Task assignment
For More Details : http://aircconline.com/ijdps/V10N3/10319ijdps01.pdf
Volume Link : http://airccse.org/journal/ijdps/current2019.html

7. REFERENCES
[1] H.-C. Hsiao, H.-Y. Chung, H. Shen and Y.-C. Chao, "Load Rebalancing for Distributed File
Systems in Clouds," IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 5, pp.
951-962, 2013.
[2] E. Y. Daraghmi and S. M. Yuan, "In-domain neighborhood approach to heterogeneous
dynamic load balancing in real world network," in 14'th International Conference on Parallel and
Distributed Computing, Applications and Technologies (PDCAT'13), Taipei, Taiwn, 2013.
[3] C. P. A. a. P. Berenbrink., "Distributed selfish load balancing with weights and speeds.," in
The 2012 ACM symposium on Principles of distributed computing, New York, USA, 2012.
[4] J. Bahi, R. Couturier and F. Vernier, "Synchronous Distributed Load Balancing on Totally
Dynamic Networks," in Parallel and Distributed Processing Symposium, 2007.
[5] E. Luque, A. Ripoll and A. C. a. T. Margalef, "A distributed diffusion method for dynamic
load balancing on parallel computers," in Euromicro Workshop on Parallel and Distributed
Processing,1995.
[6] P.Neelakantan, "Decentralized Load Balancing In Heterogeneous Systems Using Diffusion
Approach," International Journal of Distributed and Parallel systems (IJDPS), vol. 3, no. 1, pp.
229 -239, 2012.
[7] C.-C. Hui and S. Chanson, "A hydro-dynamic approach to heterogeneous dynamic load
balancing in a network of computers," in Proceedings of the 1996 International Conference on
Parallel Processing Software., 1996.
[8] G. Cybenko, "Dynamic load balancing for distributed memory multiprocessors," Journal of
Parallel and Distributed Computing, vol. 7, no. 2, pp. 279-301, 1989.
[9] J. E. Boillat, "Load balancing and Poisson equation in a graph," Concurrency: Practice and
Experience, vol. 2, no. 4, pp. 289-313, 1990.
[10] "Google File System," [Online]. Available:
http://en.wikipedia.org/wiki/Google_File_System.
[11] R. N. Calheiros, R. Ranjan, A. Beloglazo, C. A. F. D. Rose and R. Buyya, "CloudSim: a
toolkit for modeling and simulation of cloud," SOFTWARE – PRACTICE AND EXPERIENCE,
vol. 41, no. 1,pp. 23-50, 2010.
[12] R. M. I. Stoica, D. Liben-Nowell, D. R. Karger, M. F. Kaashoek, F. Dabek and H.
Balakrishnan, "Chord: a Scalable Peer-to-Peer Lookup Protocol for Internet Applications," in
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols,
San Diego, California,USA, 2001.

8. DESIGN AND ANALYSIS OF SECURE SMART HOME FOR
ELDERLY PEOPLE
Mayada Elsaid, Sara Altuwaijri, Nouf Aljammaz and Anees Ara
Computer Science Department, College of Computer & Information Sciences, Prince
Sultan University, Riyadh, Saudi Arabia
ABSTRACT
Internet of Things (IoT) technology is used to enhance the safety of the elderly living in smart
home environments and to help their caregivers. The daily behaviour of the elderly people is
collected using IoT sensors and then evaluated to detect any abnormal behaviour. This research
paper analyzes the smart home based anomaly detection system from a security perspective, to
answer the question whether it is reliable and secure enough to leave elderly people alone in their
smart homes. In this direction comparative analysis of literature is done to identify the potential
security breaches on all layers of an IoT device. Further, this paper proposes a secure smart home
model, built using Cisco Packet Tracer to simulate a network of IoT devices in a smart home
environment. Consequently, a list of security countermeasures is proposed to protect the IoT
devices from the identified attacks. .
KEYWORDS
Cyber physical systems, anomaly detection system, intrusion detection system, secure smart
home, IoT.
For More Details : http://aircconline.com/ijdps/V10N6/10619ijdps01.pdf
Volume Link : http://airccse.org/journal/ijdps/current2019.html

9. REFERENCES
[1] Aran, O., Sanchez-Cortes, D., Do, M. T., & Gatica-Perez, D. (2016, October). "Anomaly
detection in elderly daily behavior in ambient sensing environments". In International Workshop
on Human Behavior Understanding (pp. 51-67). Springer, Cham.
[2] Paudel, R., Dunn, K., Eberle, W., & Chaung, D. (2018, May). "Cognitive Health Prediction
on the Elderly Using Sensor Data in Smart Homes". In The Thirty-First International Flairs
Conference.
[3] Hoque, E., Dickerson, R. F., Preum, S. M., Hanson, M., Barth, A., & Stankovic, J. A. (2015,
June). "Holmes: A comprehensive anomaly detection system for daily in-home activities". In
2015 International Conference on Distributed Computing in Sensor Systems (pp. 40-51). IEEE.
[4] Hsu, Y. L., Chou, P. H., Chang, H. C., Lin, S. L., Yang, S. C., Su, H. Y., ... & Kuo, Y. C.
(2017). "Design and implementation of a smart home system using multisensor data fusion
technology". Sensors, 17(7), 1631.
[5] Pal, D., Triyason, T., & Funikul, S. (2017, December). Smart homes and quality of life for
the elderly: A systematic review. In 2017 IEEE International Symposium on Multimedia (ISM)
(pp. 413-419). IEEE.
[6] Lê, Q., Nguyen, H. B., & Barnett, T. (2012). "Smart homes for older people: Positive aging
in a digital world". Future internet, 4(2), 607-617.
[7] Boyanov, L., & Minchev, Z. (2014). "Cyber Security Challenges in Smart Homes". Volume
38: Cyber Security and Resiliency Policy Framework,IOS Press Ebooks
[8] Paudel, R., Eberle, W., & Holder, L. B (2018). "Anomaly Detection of Elderly Patient
Activities in Smart Homes using a Graph-Based Approach". In: Proceedings of the 2018
International Conference on Data Science, pp. 163–169. CSREA .
[9] Rao, T. A. "Security Challenges Facing IoT Layers and its Protective Measures".
International Journal of Computer Applications, 975, 8887.
[10] Lin, H., & Bergmann, N. (2016). "IoT privacy and security challenges for smart home
environments". Information, 7(3), 44.
[11] Ara, A., Al-Rodhaan, M., Tian, Y., & Al-Dhelaan, A. (2015). "A secure service
provisioning framework for cyber physical cloud computing systems". arXiv preprint
arXiv:1611.00374.
[12] Mtshali, P., & Khubisa, F. (2019, March). "A Smart Home Appliance Control System for
Physically Disabled People". In 2019 Conference on Information Communications Technology
and Society (ICTAS) (pp. 1-5). IEEE.

10. [13] Karimi, K., & Krit, S. (2019, July). "Smart home-Smartphone Systems: Threats, Security
Requirements and Open research Challenges". In 2019 International Conference of Computer
Science and Renewable Energies (ICCSRE) (pp. 1-5). IEEE.
[14] Adiono, T., Tandiawan, B., & Fuada, S. (2018). "Device protocol design for security on
internet of things based smart home". International Journal of Online Engineering (iJOE),
14(07), 161-170.
[15] Sultana, S. N., Ramu, G., & Reddy, B. E. (2014). "Cloud-based development of smart and
connected data in healthcare application". International Journal of Distributed and Parallel
Systems, 5(6), 1.
AUTHORS BIOGRAPHY
Mayada Elsaid is a senior Software Engineering ( Cyber Security) student in Prince Sultan
University. She is an IEEE member and chair in IEEE-Student Chapter. Her areas of interest and
research are cyber physical systems security and IoT. She has presented security and business
process management papers in local conferences and research forums.
Sara Altuwaijri is a bachelor student, majoring in Software Engineering (Cyber Security) at
Prince Sultan University. She’s currently leading two clubs in the university by arranging events
and bootcamps that are related to many topics of computer science. She’s the president of Edtech
club and the Vice Chair if IEEE chapter at PSU. She received nano degrees in Artificial
Intelligence and Self-driving cars. Her research interests include security & privacy in IoT and
cyber physical systems.
Nouf Aljammaz is a senior Computer Science (Cyber Security) student focused on improving
facility security through diligent approach and sense of personal responsibility. Resilient
individual trained in security. Her research interest includes security domains related to risks
management, optimization techniques relates to asset protection and threat minimizations.
Anees Ara received her BSc in Computer Science and MSc in Mathematics with Computer
Science from Osmania University, India in 2005 and 2007 respectively. She has received her
PhD degree from King Saud University and she is currently working as Assistant Professor at
College of Computer and Information Sciences, Prince Sultan University, Kingdom of Saudi
Arabia. She is an active member of Security Engineering Lab, Prince Sultan University, KSA
and IEEE, computing society. In addition, she is an active reviewer of international journals. Her
research interests are broadly divided into privacy and security, which are related to cloud
computing, cryptograph, smart environment, cyber physical systems and big data.