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Go to Editorial ManagerWith the substantial growth of mobile applications and the emergence of cloud computing concepts, therefore mobile Cloud Computing (MCC) has been introduced as a potential mobile service technology. Mobile has limited resources, battery life, network bandwidth, storage, and processor, avoid mobile limitations by sending heavy computation to the cloud to get better performance in a short time, the operation of sending data, and get the result of computation call offloading. In this paper, a survey about offloading types is discussed that takes care of many issues such as offloading algorithms, platforms, metrics (that are used with this algorithm and its equations), mobile cloud architecture, and the advantages of using the mobile cloud. The trade-off between local execution of tasks on end-devices and remote execution on the cloud server for minimizing delay time and energy saving. In the form of a multi-objective optimization problem with a focus on reducing overall system power consumption and task execution latency, meta-heuristic algorithms are required to solve this problem which is considered as NP-hardness when the number of tasks is high. To get minimum cost (time and energy) apply partial offloading on specific jobs containing a number of tasks represented in sequences of zeros and ones for example (100111010), when each bit represents a task. The zeros mean the task will be executed in the cloud and the ones mean the task will be executed locally. The decision of processing tasks locally or remotely is important to balance resource utilization. The calculation of task completion time and energy consumption for each task determines which task from the whole job will be executed remotely (been offloaded) and which task will be executed locally. Calculate the total cost (time and energy) for the whole job and determine the minimum total cost. An optimization method based on metaheuristic methods is required to find the best solution. The genetic algorithm is suggested as a metaheuristic Algorithm for future work.
Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In this article, a summary of heuristic and meta-heuristic methods for solving the task scheduling optimization in cloud-fog systems is presented. The cost and time aware scheduling methods for both bag of tasks and workflow tasks are reviewed, discussed, and analyzed thoroughly to provide a clear vision for the readers in order to select the proper methods which fulfill their needs.
Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mobile vehicles. Several studies have tackled the task offloading problem in the VFC field. However, recent studies have not carefully addressed the transmission path to the destination node and did not consider the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives under deadline constraint by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Road Side Units (RSUs) x-Vehicles Mutli- Objective Computation offloading method (RxV-MOC) is proposed, where an elite of vehicles are utilized as fog nodes for tasks execution and all vehicles in the system are utilized for tasks transmission. The well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the RxV-MOC has reduced significantly the energy consumption and latency for the VFC system in comparison with First-Fit algorithm, Best-Fit algorithm, and the MOC method.
Every day, a tremendous amount of image data is generated as a result of recent advances in imaging and computing technology. Several content-based image retrieval (CBIR) approaches have been introduced for searching image collections. These methods, however, involve greater computing and storage resources. Cloud servers can address this issue by offering a large amount of computational power at a low cost. However, cloud servers are not completely trustworthy, and data owners are concerned about the privacy of their personal information. In this research, we propose and implement a secure CBIR (SCBIR) strategy for searching and retrieving cipher text image databases. In the proposed scheme, the extract aggregated feature vectors to represent the related image collection and use a safe Asymmetric Scalar-Product-Preserving Encryption (ASPE) approach to encrypt these vectors while still allowing for similarity computation. To improve search time, all encrypted features are recursively clustered using the k-means method to create a tree index. The results reveal that SCBIR is faster at indexing and retrieving than earlier systems, with superior retrieval precision and scalability. In addition, our paper introduces the watermark to discover any illegal distributions of the images that are received by unlawful data users. Particularly, the cloud server integrates a unique watermark directly into the encrypted images before sending them to the data users. As a result, if an unapproved image copy is revealed, the watermark can be extracted and the unauthorized data users who spread the image can be identified. The performance of the proposed scheme is proved, while its performance is demonstrated through experimental results.
Water scarcity, drought, and population growth accompanying climate change are dangerous factors with serious consequences related to potable water file unless appropriate action is taken urgently to deal with these issues, especially with large populations in the major cities as well as the suburban areas. This work presents an enhanced wide area network for efficient management of the freshwater in the major cities. Hence, it adopts Mosul city as a typical case that contains about 100 residential districts that require 100 sites of water monitoring in the different locations in the city where each site owns three different types of water sensors (water flow, water level, and pressure) in addition to the video surveillance application. The water station sites send the data to the control and monitoring center of the water. The collected data is processed and analyzed by public cloud or private cloud for control and monitoring purposes. The suggested communication network addresses the requirements of the water section applications in terms of monitoring in real-time. This work addresses the WiMAX system as a communication network infrastructure to handle the advantages of resilience, low-cost maintenance, and expansion The suggested network offered excellent behavior in terms of latency (maximum latency is less than 57 msec) and data traffic of the adopted applications.
Searchable symmetric encryption (SSE) is a robust cryptographic method that allows users to store and retrieve encrypted data on a remote server, such as a cloud server, while maintaining the privacy of the user’s data. The technique employs symmetric encryption, which utilizes a single secret key for both data encryption and decryption. However, extensive research in this field has revealed that SSE encounters performance issues when dealing with large databases. Upon further investigation, it has become apparent that the issue is due to poor locality, necessitating that the cloud server access multiple memory locations for a single query. Additionally, prior endeavors in this domain centered on locality optimization have often led to expanded storage requirements (the stored encrypted index should not be substantially larger than the original index) or diminished data retrieval efficiency (only required data should be retrieved).we present a simple, secure, searchable, and cost-effective scheme, which addresses the aforementioned problems while achieving a significant improvement in information retrieval performance through site optimization by changing the encrypted inverted index storage mechanism. The proposed scheme has the optimal locality O(1) and the best read efficiency O(1)with no significant negative impact on the storage space, which often increases due to the improvement of the locality. Using real-world data, we demonstrate that our scheme is secure, practical, and highly accurate. Furthermore, our proposed work can resist well-known attacks such as keyword guessing attacks and frequency analysis attacks.
Due to the recent improvements in imaging and computing technologies, a massive quantity of image data is generated every day. For searching image collection, several content-based image retrieval (CBIR) methods have been introduced. However, these methods need more computing and storage resources. Cloud servers can fill this gap by providing huge computational power at a cheap price. However, cloud servers are not fully trusted, thus image owners have legal concerns about the privacy of their private data. In this paper, we proposed and implemented a privacy-preserving CBIR (PP-CBIR) scheme that allows searching and retrieving image databases in a cipher text format. Specifically, we extract aggregated feature vectors to represent the corresponding image collection and employ the asymmetric scalar-product-preserving encryption scheme (ASPE) method to protect these vectors while allowing for similarity computation between these encrypted vectors. To enhance search time, all encrypted features are clustered by the k-means algorithm recursively to construct a tree index. Results show that PP-CBIR has faster indexing and retrieving with good retrieval precision and scalability than previous schemes.
The Internet of Things (IoT) has become a major enabler for sustainable development and has begun to have an impact on society as a whole. Marshes are significant ecosystems for the environment that are essential to biodiversity support and ecological equilibrium. However, environmental changes and human activity are posing an increasing threat to these fragile ecosystems. An Internet of Things (IoT)-based marsh monitoring system was created and put into operation to gather data in real-time on a variety of environmental factors, such as wind speed, CO2 and hydrogen levels, temperature, humidity, voltage, and current. The system makes use of a network of sensors spread out throughout the marsh, which may promote sustainable development. send data to a central node for processing before sending it to a platform hosted in the cloud. After that, an interactive online application is used to visualize the data, giving stakeholders important information about the condition and health of the marsh. Because the suggested system makes it possible to monitor and manage marsh ecosystems effectively, it may promote sustainable development.
Nowadays, there are no accurate records of the various quantities of fuel being dispensed at the Iraqi fuel stations. All such reports are usually paper-based and are missing the required precision to control this valuable commodity, which could lead to misuse or illegal sale of fuel. This paper presents a control system based on RFID technology to monitor the supply and dispensing of vehicle fuel in Baghdad. The system consists of RFID readers attached to fuel dispensers and pumps, and RFID tags assigned to the vehicles and the trucks used for delivering fuel to the fuel stations. A hardware part is connected to conventional fuel dispensers and machines, located at both the stations and the fuel refineries or depots, which makes them work under the control of the RFID system, without the need to rebuild new dispensers. The designed system database is a centralized one located on a cloud server, in order to allow fuel stations to communicate with it and do the required transactions. Throughout this system, different reports can be generated, which can give important online statistics about the movement of fuel supplies over the city.
Searchable encryption (SE) is an interesting tool that enables clients to outsource their encrypted data into external cloud servers with unlimited storage and computing power and gives them the ability to search their data without decryption. The current solutions of SE support single-
Upkeeping the Battery State-Of-Charge (SoC) and its life are of great significance in Battery Electric Vehicle (BEV) & Hybrid Electric Vehicles (HEV). This is possible by integrating Solar Photovoltaic Panels (PPs) on the Roof-top of the BEVs & HEVs. However, unlike Solar Powered Vehicle Charging stations and other PV applications where the solar panels are installed in such a way to extract the maximum Photon energy incident on the panel, vehicle Roof-top mount Solar PPs face many challenges in extracting maximum Power due to partial shading issues especially under dynamic conditions when passing under trees, high rise buildings and cloud passages. This paper proposes a new strategy called “Super-capacitor Assisted Photovoltaic Array”. In which Photovoltaic Modules are integrated with Super-capacitors to improve the transient performance of the Photovoltaic Array system. The design of proposed Super-capacitor Assisted PV array is validated & its performance is compared with conventional PV array in Matlab/ Simulink environment.
This work concerns creating a monitoring system for a smart hospital using Raspberry Pi to measure vital signs. The readings are continually sent to central monitoring units outside the room instead of being beside the patients, to ensure less contacting between the medical staff and patients, also the cloud is used for those who leave the hospital, as the design can track on their medical cases. Data presentation and analysis were accomplished by the LabVIEW program. A Graphical User Interface (GUI) has been created by the Virtual-Instrument (VI) of this program that offer real-time access to monitor patients’ measurements. If unhealthy states are detected, the design triggers alerts and sends SMS message to the doctor. Furthermore, the clinicians can scan a QR code (which is assigned to each patient individually) to access its real-time measurements. The system also utilizes Electrocardiography (ECG) to detect abnormalities and identify specific heart diseases based on its extracted parameters to encourage patients to seek timely medical attention, while aiding doctors in making well-informed decisions. To evaluate the system’s performance, it is tested in the hospital on many patients of different ages and diseases as well. According to the results, the accuracy measurement of SpO2 was about 98.39%, 97.7% for (heart rate) and 98.7% for body temperature. This shows that the system can offer many patients receiving health services from various facilities, and it ensures efficient data management, access control, real-time monitoring, and secure patient information aligning with healthcare standards.
Recently, the incorporation of state-of-the-art technology such as Electronic Healthcare Records (EHRs), networks, and cloud computing has transformed the traditional healthcare system. However, security problems have arisen as a result of the integration of technology. Secure remote user authentication is a core part of the healthcare system to validate the user's identification via an unsecure communication network. Since then, several remote user authentication schemes have been presented, each with its own set of pros and limitations. As a result, security, malicious attacks and privacy concerns are considered one of the main challenges related to the healthcare system. In this paper, we propose a safe user authentication scheme for patients in the healthcare system that overcomes these flaws and confirms the security of the proposed work using scyther, a formal security tool. In the healthcare environment, our work provides an effective means to construct an environment capable of setting, registering, storing, searching, analyzing, authentication, and verifying electronic healthcare information in order to protect the information of patients. Furthermore, our suggested scheme uses symmetric encryption based on the crypto- hash function for accessing the anomaly of the patient's identity and One-Time Password (OTP). Towards the end of the study, the performance analysis results indicate a delicate balance of security and performance that is frequently lacking in previous works.
In the era of modern trends such as cloud computing, social media applications, emails, mobile applications, and URLs that lead to increased risks for defrauding authorized users, and then the attackers try to gain illegal access to accounts of users through a malicious attack. The phishing attack is one of the dangerous attacks caused to access of authorized account illegally way. The finances, business, banking, and other sensitive in states are faces by this type of attacks due to the important information they have. In this paper, we propose a secure verification scheme that can overcome the above-mentioned issues. Additionally, the proposed scheme can resist famous cyberattacks such as impersonate attacks, MITM attacks. Moreover, the proposed scheme has security features like strong verification, forward secrecy, user’s identity anomaly. The security analysis and the experimental results proved the strongest of the proposed scheme compared with other related works. Finally, our proposed scheme balanced between the performance and the security merits.
This work addresses the critical need for secure and patient-controlled Electronic Health Records (EHR) migration among healthcare hospitals’ cloud servers (HHS). The relevant approaches often lack robust access control and leave data vulnerable during transfer. Our proposed scheme empowers patients to delegate EHR migration to a trusted Third-Party Hospital (TTPH); which is the Certification Authority (CA) while enforcing access control. The system leverages asymmetric encryption utilizing the Elliptic Curve Digital Signature Algorithm (ECDSA), EEC and ECDSA added robust security and lightness EHR sharing. Patient and user privacy is managed due to anonymity through cryptographic hashing for data protection and utilizes mutual authentication for secure communication. Formal security analysis using the Scyther tool and informal analysis was conducted to validate the system’s robustness. The proposed scheme achieved EHR integrity due to the verification of the communicated HHS and ensuring the integrity of the HHS digital certificate during EHR migration. Ultimately, the result achieved in the proposed work demonstrated the scheme’s high balance between data security and accuracy of communication, where the best result obtained represented 7.7/ ms as computational cost and 1248 /bits as communication cost compared with the relevant approaches.
In this work, a healthcare monitoring system-based Internet of Medical Things (IoMT) is proposed, implemented, analyze it by artificial intelligence using fuzzy logic. Atmega microcontroller was used to achieve the function of the proposed work and provide the area for monitoring and Analytic(decision) to the caretakers or doctors through putting the results in the platform. In this paper, the heart rate pulse sensor and infrared temperature sensor are chosen, which give skin temperature and room temperature to provide their results to the caretaker. The decision that gives the patient is in a normal state, or the fuzzy logic does an abnormal state or risk state. The fuzzy logic is used for it accurate and fast in processing data and gives a result very closer to the reality in smart health services. IoMT enables the doctors and caretakers to monitor the patient easily at any time and any place by using their intelligent laptops, tablets, and phones. Finally, the proposed system can contribute to the construction of a wide healthcare monitoring system in the unit or in the department that follows on for the hospital. Therefore, Doctors can improve the accuracy of the diagnosis, as they receive all the patient data necessary.