International Journal of Cloud Computing (12 papers in press)
Genetic and static algorithm for task scheduling in cloud computing
by Jocksam Gonçalves De Matos, Carlos Heitor Pereira Liberalino, Carla Katarina De Monteiro Marques
Abstract: Technological advancement has required ever more computing resources. In this context the cloud computing emerges as a newparadigm to meet this demand, though its resources are physically limited due to the growing data traffic that the system may be subject. The task scheduling aims to distribute tasks in order to make them more efficient in the use of computing resources. Thus, this paper aims to propose a solution to the task scheduling problem in cloud computing in order to reduce the processing time of the tasks and the number of virtual machines. This algorithm was designed from heuristic solution with the aid of a static algorithm. The proposed algorithm was mainly inspired by the set partitioning problem that aims to reduce the number of virtual machines. The metaheuristic genetic algorithm was used in the first stage of the algorithm, in order to reduce the processing time of the tasks. The static algorithm is designed to solve the set partitioning problem. Their performance was compared with two algorithms, classic and heuristic. The CloudSim, a computer simulator in the cloud that has characteristics and attributes of a real cloud was used as a way to evaluate the proposed algorithm, along with realistic workloads in experiments that showed the algorithms behavior under different conditions of use.
Keywords: distributed computing; cloud computing; scheduling; metaheuristic.
Review of Remote Data Integrity Auditing Schemes in Cloud Computing: Taxonomy, Analysis, and Open Issues
by JAYA R.A.O. GUDEME, Syam Kumar Pasupuleti, Ramesh Kandukuri
Abstract: Cloud storage provides reliable and resilient storage infrastructure for users to store data remotely based on pay-as-you-go pricing model. Presently, many data owners in academic and business environment are choosing cloud for storing their data in the cloud to save costs. Cloud storage provides many benefits to data owners such as low capital costs, scalability, and access of data from anywhere, anytime, irrespective of location and device. Despite these appealing benefits, storage service brings security challenges such as confidentiality, integrity and availability as outsourced data is not always trustworthy due to loss of physical control and possession over data. One of the primary concern is the integrity of data stored in the cloud. To address the remote data integrity, many researchers have focused on Remote Data Integrity Auditing (RDIA) techniques. In this paper, we give an extensive review of remote data integrity auditing techniques in the cloud computing. In our review, we present a thematic taxonomy of remote data integrity auditing techniques, investigate similarities and differences, and finally discuss critical issues to be addressed for efficient and secure designing of remote auditing protocols for cloud data storage in future research.
Keywords: Cloud computing; Cloud storage; Integrity; Remote data auditing; Provable Data Possession; PDP; Proof of Retrievability; PoR.
A Hybrid Method for Improving Quality of Service (QoS) in Constraint-Based Availability in the Cloud for SMEs
by Alireza Nik Aein Koupaei
Abstract: Research in cloud computing has gone through rapid development duringrnthe last decade and has emerged as a key service of utility or on-demand computing. Small and medium-sized enterprises (SMEs) assure economic growth in the world. In the main, many SMEs are struggling to survive in an ongoing global recession and are often unwilling to use research results and new technologies for business and learning. Cloud computing provides many opportunities and could help companies expand and improve their business and use technology more resourcefully. The resource provision is an essentialrnperspective of cloud computing technology to provide the QoS (quality of service) in cloud computing. It is used as an alternative to SLA (Service Level Agreement). In this paper, we are going to present a new cloud hybrid method and architecture to improve, the QoS and Availability under the Cloud computing environment. Additionally, issues regarding the extent effect of cloud computing in SMEs have been highlighted. In conclusion, criticalrnfuture challenges in the area are addressed.
Keywords: Cloud Computing; SMEs; Availability; Service Level Agreement (SLA).
Adaptive and Intelligent framework of data protection techniques for cloud storage
by Kanimozhi Vedharajan
Abstract: Cloud Computing is the latest technology that revolutionize the mobile and Information Technology field. Mobile phone cloud application users are hesitating to move their information from their mobile to the cloud service supplier due to increasing information security and privacy concern. When People try to store a lot of files inside their storage, they need to check the storage limit. To reduce the storage size to minimum user need to use some compression technique. In the proposed technique the user original data is taken, in the original data watermarking technique is applied and then the data is compressed to reduce the storage size of the data. Then some secrete message is embedded with the image for the authentication of the data and these authenticated data is involved in security processes of Spector encryption. This encrypted data is divided into n pieces and each piece of data is going to be stored in a different storage location of the cloud. When any intruder wants to take the original data it is impossible because different location of the data pieces and encryption technology. When downloading the data from the cloud the data includes the reversed process of all and the original data is received. In the proposed technique, a mobile information security cryptography model and J-bit encoding (JBE) for data compression is planned to encounter this downside. The data compression algorithm will manipulates each bit of data inside file to minimize the size without losing any data after decoding which is classified to lossless compression. This basic algorithm is intended to be combining with other data compression algorithms to optimize the compression ratio. The performance of this algorithm is measured by comparing combination of different data compression algorithms. With the technical advancement in the mobile and cloud computing, an intelligent data protection technique using Spector encryption with J-bit compression technique is proposed for Mobile information Security.
Keywords: J-bit encoding; Spector Encryption; Mobile cloud computing; Watermarking; Data compression; Secret message embedding.
IAM with PostLogin Authentication for Service Usage Authorization in Cloud Computing
by Aniruddha Rumale, Dinesh Chaudhari
Abstract: When user login into the cloud service, access to sensitive data and financial- transactions need postlogin authentication of a user to authorize him/her to grant usage rights for such services. This is necessary because theft of username and password by an inadvertent user can give him complete access to the account, causing great trouble to the legitimate user. To avoid any theft or manipulation of sensitive information like user profile, or to avoid any inadvertent execution of financial transactions, Identity and access management of CSP (Cloud Service Provider) need to do postlogin authentication of a user. This can be done using some randomly generated password, different from the login password. Postlogin authentication authorizes user the complete access to use sensitive part or service of a user account. Postlogin authentication of users for service usage authorization can be done by (i) Sending OTP (One Time Password) to a user over some other safe communication network, (ii) Throwing some challenging intelligent designs like a game for playing, quest for solving, etc.Postlogin authentication guarantees safety of the user's sensitive data and services even after the theft of username and login-password. An intruder, in this case, neither get any access to user's sensitive data nor get any access to financial services; to commit any harm to user or user's account. The paper outlines in brief the generic IAM process within the context of Cloud computing. It also emphasizes the need of postlogin authentication of a user for service usage. OTP is one popular postlogin authentication mean used by many CSPs. Paper proposes variable length OTP and some intelligent designs for postlogin authentication.
Keywords: Cloud Computing; Identity and Access Management(IAM); Cloud Security; Authentication and Authorization;rnOTP; SSO; Trusted Computing.
Optimal Allocation of Cloud Multi-Tenant Platform Infrastructure Resources
by Oleksiy Ignatyev
Abstract: Infrastructure resources optimization is a significant challenge in multi-tenant cloud environment. A system and associated algorithm and processes to enable a multi-tenant platform operator or administrator to make more optimal decisions with regards to the allocation of platform infrastructure resources (such as computational capabilities, data storage, etc.) among one or more tenants or accounts are provided. In particular, we construct a data signature for a set of identified users, accounts, or tenants, where the signature contains data regarding the user, account, or tenants consumption of platform infrastructure resources. Later tenants signatures are being used to accomplish cloud infrastructure resources optimization in multi-tenant environment. An innovative algorithm for cloud infrastructure resources optimization in multi-tenant environment is introduced in current paper.
Keywords: cloud computing; multi-tenant architecture; cloud infrastructure; Software-as-a-Service (SaaS); data storage; computational processing power; resources optimization.
Experimental Analysis and Comparative Study of Secure Data Outsourcing Schemes in Cloud.
by V. Sudarsan Rao
Abstract: When customers are transfering their private data to any third party, then there is much responsibility of both security and compliance. The outsourcing process is computationally secure if it is performed without unveiling to the other external agent or cloud, either the original data or the actual solution to the computations. Secure multiparty computation computes a certain function\r\nwithout revealing their private secret information. Homomorphic encryption is another solution that can deal with this situation. In homomorphic encryption, ciphertext (data in encrypted format) should be sent to the cloud, the computations are made on the ciphertext, and the result of this computation is a ciphertext form itself. If the result of the computation is decrypted, then the correct plaintext result must be obtained.\r\nIn this paper, we summarized our proposed secure outsourcing computing protocols. As a cloud application, our proposed protocols encrypt data by different users and further is transformed to cloud. By utilizing our protocols, we performed experimental analysis on virtual cloud to examine the novelty in terms of computational and communication complexity. Our implementations involve both CPU and GPU based simulation results. We improved our adopted procedure to achieve better speed-up and security.
Keywords: Private information parameters; Scientific computation; Confidential data; Secure outsourcing; Cloud computing; Privacy.
An Incremental and Distributed Inference Method for Large Scale Ontologies over SPARK
by Mohamed Oubezza
Abstract: The study of the semantic interoperability and the reasoning over big data is today a major challenge for researchers, especially with the birth of semantic web and deep data. The existing solutions are not yet able to satisfy the requirements of the final user especially in terms of the consistency of the results and the request execution time. To do this we need an approach based on an ontology and a distributed and scalable system. Several studies have been done on the reasoning over large scale Ontologies, most are based on Hadoop and Map Reduce or non-incremental, ie they recalculate the result at the arrival of new data. In this paper we propose an incremental and distributed method of reasoning over very large OWL Ontologies based on SPARK, which offers a reduced execution time as it loads the RDF triplets in memory and not in disk. Our method allows creating Transfer Inference Forest (TIF) and Effective Assertionnal Triples (EAT) to reduce disk space and simplify and accelerate the reasoning process.
Keywords: Semantic Web; Ontology reasoning; OWL; OWL Horst; SWRL; SPARQL; Hadoop; SPARK.
User Support as Moderator for Cloud Computing User Satisfaction
by Tor Guimaraes, Ketan Paranjape
Abstract: Cloud Computing (CC) promises to provide quicker, easier, and less expensive computing services supporting E-Commerce. To ensure that CC is also able to maintain or enhance customer satisfaction, this study addresses the factors leading to higher user satisfaction with SaaS applications websites. The proposed model defines and empirically tests these relationships, including the moderating effect of user support. Data collected from 1257 users/customers using the order entry systems of 176 client organizations available through four SaaS providers were analyzed. Results confirm the importance of the proposed success factors for user satisfaction with the CC vendor websites. Management of CC application risks, knowledge about the service provider, and effective data management respectively explained significant percentages of the variance in user satisfaction with the CC vendor website. The positive impact of user support is also confirmed. The results provide the basis for several insights and recommendations for managers and future research.
Keywords: Cloud Computing; E-commerce; user satisfaction; SaaS success factors; user support.
A dynamic strategy-proof algorithm for allocation and pricing of cloud services
by Temidayo Oluwatosin OMOTEHINWA, Joseph Shuaibu SADIKU
Abstract: The current increase in cloud service demand necessitates the need for an efficient cloud market mechanism for cloud service allocation and pricing. The fixed pricing approach has been proven not to be the best as it is mostly provider bias. Also, dynamic trading systems are mostly single sided and computational intensive in nature. They are either seller-centric or consumer-centric. This gives undue advantage to either the buyer or the seller. In this paper, we present a dynamic strategy-proof algorithm for allocation and pricing. The algorithm relies on market history to forecast a benchmark price to ensure truthful valuation from the market participants. The algorithm also ensures that the utility is evenly distributed between the buyer and the seller. The utility is the difference between the buyers maximum offer and the sellers minimum acceptable price. The results of the experimental studies carried out shows that: (i) the budget limits of the buyers with successful allocations were not exceeded (ii) and only market participants with truthful offers and bids were allocated services, (iii) the utility is higher when there is no strategy-proof for preventing overbid and that there is at least a 50% increase in price per unit when there is no strategy-proof to prevent overbid, (iv) in terms of computational efficiency, the algorithm converges in polynomial time with a worst-case running time of O(n^2).
Keywords: cloud computing; resource allocation; resource pricing; cloud services; algorithm; strategy-proof.
A Scalable Network-Aware Virtual Machine Allocation Strategy in Multi-Datacentre Cloud Computing Environments
by Marwa Abdelaal, Gamal Ebrahim, Wagdy Anis
Abstract: Virtual machine provisioning in multi-datacentre cloud computing environments is a challenging problem. However, most current virtual machine management strategies ignore their effect on cloud network. In this paper, a scalable network-aware resource allocation strategy is proposed that dynamically allocates virtual machines in cloud computing environments while minimising the overall cost. It is mainly utilised at the cloud service provider that has a large number of datacentres. Several important parameters have been taken into consideration that are mainly ignored in previous related studies. Additionally, Software-Defined Network (SDN) has been adopted in the proposed strategy. Simulation studies have been conducted to evaluate the performance of the proposed strategy. Simulation results show a reduction in the utilisation in the valuable upper-layer links in datacentres that resulted mainly because of favouring lower-cost links during virtual machine allocation process. Additionally, the proposed strategy is able to cope with the dynamic nature of the allocation process. More importantly, the proposed strategy avoids false allocation at the datacentres of the cloud service provider.
Keywords: Cloud Computing; Datacentre; Software-Defined Network; Virtual Machine.
Special Issue on: ICACB18 Advanced Computing and Communication Systems
A HYBRID ENCRYPTION METHOD HANDLING BIG DATA VULNERABILITIES
by Priyanka G, Anisha Lal
Abstract: As Big Data hits the maximum number of companies in all domains, secured data transfer can be done by cryptography. With increasing threats to Big Data, the security must focus on to avoid the attackers from the formation of any pattern to gain access to the information. Big data deals with the linguistic data which consists of low secured data and high secured data as well. Hence, the system should focus on providing multi-fold security and should avoid high-security common to all data categories. This paper presents a hybrid model for Big Data that ensures Data Confidentiality, Data Integrity, Access Control and Sequential Freshness by combining three symmetric key algorithms AES, DES and Blowfish for the encryption and decryption process in any desired order. Based on the level of security the combination of the algorithms can vary. This method of encryption and decryption process ensures safe data transformation between source and destination.
Keywords: Hybrid; Encryption;Big Data.