Ubiquitous Network Access Research Articles

Secure Date Storage Using ECC Encryption with Verifiable Data Sharing in Cloud

Cloud data storage has become increasingly popular, but the security and privacy of data stored in the cloud remain major concerns. Cloud computing is the most feasible approach for implementing Digital Twin services since it has prodigious advantages. It provides on demand services, computing resources, ubiquitous network access, etc., making it suitable for the next-generation information technology architecture. In cloud-assisted data storage environments, the data owners generate data from physical assets and disseminate it to the cloud server.

Innovative Trends in the 6G Era: A Comprehensive Survey of Architecture, Applications, Technologies, and Challenges

While the fifth-generation mobile network is being commercialized worldwide, researchers have recently started looking towards the next generation, called the 6G network. Unlike 5G and previous generations of wireless technologies designed to improve network performance for greater bandwidth, lower latency and greater reliability, 6G ecosystems is considered a platform conducive to innovations in the fields of computing, artificial intelligence, connectivity and sensors, virtualization and more. It is designed to meet the requirements of higher global coverage, greater spectral efficiency, a reduced carbon footprint, with an emphasis on sustainability, equity, trust and security through unprecedented architectural evolutions and technology. 6G will be an integrated network system that includes a traditional terrestrial mobile network, space network, and underwater network to provide ubiquitous network access. Even if there are studies on vision of 6G network that have already been published, there is still a significant amount of ground to cover. There is no decision made yet regarding anything and nothing has been ruled out. The focus of this study is to identify a complete picture of changes in architectures, technologies, and challenges that will shape the 6G network. We hope the research results will provide indications for further studies on 6G ecosystems.

Traffic Engineering for Software-Defined LEO Constellations

The emerging low earth orbit (LEO) satellite networks are expected to provide the world’s most advanced Internet services. Besides, terrestrial networks are in constant evolution and already moving to embrace the relatively new paradigm of software defined networking (SDN). In this paper, we take the advantages of SDN features and leverage traffic engineering (TE) to enhance the ISL performance in broadband LEO satellite networks. We investigate unicast and multicast TE for SDN-enhanced LEO constellations to empower satellite-based Internet services. In LEO satellite networks, unicast supports ubiquitous network access and provides basic network services, while multicast features superior satellite-based video distribution. For unicast TE in grid ISL networks, we present a simple yet efficient k-segment routing based strategy with segment routing (SR) techniques, which can achieve near optimal max link utilization when compared with the multi-commodity flow solution. In the meanwhile, our solution eliminates routing tables and only imposes little routing information stored in packet headers. For multicast TE, we employ rectilinear Steiner trees (RSTs) to maximize bandwidth saving and exploit obstacle-avoiding rectilinear Steiner trees (OARSTs) to address the contention of multiple multicast groups. Based on RSTs and OARSTs, we propose an effective per-flow management scheme to balance traffic among multiple multicast flows in the presence of limited link capacities. Simulation results demonstrate the effectiveness and efficiency of our approaches on reducing routing information and accommodating more multicast groups.

Major Security Threats and Attacks that Facing Cloud Computing with the Main Defence Strategies

Cloud Computing (Cloud) enables ubiquitous network access to a pool of shared and configurable resources. It is based on shared services and infrastructure convergence. Cloud computing offers a slew of advantages, including the ability to store large amounts of data and a variety of services, as well as addressing the issue of scarce resources and lowering service costs. Regardless of its benefits,the shift from local to remote computing has created a slew of security concerns and challenges for both consumer and provider. Addressing and evaluating cloud computing challenges is critical. Thus, by discussing cloud computing challenges alongside available and potential solutions, users, developers, and businesses can identify pertinent and timely responses to specific threats, resulting in the best possible cloud computing-based services. The purpose of this article is to discuss the inherent difficulties associated with cloud computing and some critical solutions for overcoming them. This article extracted and analyzed seminal papers in order to contribute to the corpus of literature by highlighting several critical challenges in the cloud computing domain and shedding light on how these challenges affect a variety of domains, including users, sites, and business. The most frequently mentioned challenges include data loss, data breaches, account or service hijacking, insecure interfaces and APIs, malicious insiders, insufficient due diligence, abusive cloud service use, shared technology issues, unknown risk profile, identity theft, business model changes, lock-in, cryptography, cloud data recycling, malware, and untrusted computing. This paper addressed these issues by incorporating previously discovered solutions. There has been discussion of the implications for both researchers and practitioners.

A Distributed Survivable Routing Algorithm for Mega-Constellations With Inclined Orbits

Mega-constellations consisting of hundreds to thousands of low-earth-orbit (LEO) satellites are an attractive solution for providing global ubiquitous network access. Due to good coverage properties for populated areas, inclined orbits are gaining popularity among commercial constellations. A scalable routing algorithm with survivability plays a key role in such systems. In this paper, we propose a distributed survivable routing algorithm for mega-constellations with inclined orbits. First, the special topology characteristic of inclined constellations is identified and formalized. Based on the topology characterization, a basic X-Y routing algorithm is presented to determine multiple primary and secondary paths towards each destination utilizing the regularity of the network topology with minimal computation overhead. Then, a failure recovery mechanism which consists of a restricted flooding mechanism and a pre-detour mechanism is proposed to reduce end-to-end delay and signaling overhead in case of link failures. Besides, a partial-record loop avoidance mechanism is proposed to deal with routing loops with minimal overhead. Finally, a vector-based next hop selection mechanism is proposed to facilitate the selection of next hop while incorporating various criteria. The performance of the proposed routing algorithm is evaluated through simulation on the Starlink constellation. Simulation results show that our proposal achieves scalability by reducing signaling overhead and provides better quality of service in terms of end-to-end delay under link failures.

Hybrid Invasive Weed Optimization with Greedy Algorithm for an Energy and Deadline Aware Scheduling in Cloud Computing

Cloud computing is being envisioned to be the computing paradigm of the next generation primarily for its advantages of on-demand services, risk transference, resource pooling that is independent of location and ubiquitous network access. Service quality is allocated using various resources in the scheduling process. The deadline refers to the time period from task submission until task completion. An algorithm that has good scheduling attempts at keeping the task executed inside the constraint of the deadline. The Genetic Algorithm (GA) is a common metaheuristic that is used often in literature for procuring solutions that are either optimal or near-optimal. The Invasive Weed Optimization (IWO) is an evolutionary algorithm that is population-based with certain interesting specifications like creations of offspring that are based on the levels of fitness of the parents which increases the size of the population and generates new population by making use of the best among parents and the best among off-springs. The Greedy Algorithms will construct an object that is globally best by means of continuously choosing the option that is locally the best. In this work, a hybrid GA with the Greedy Algorithm and a Hybrid IWO with the Greedy Algorithm that has been proposed for the energy and the deadline-aware scheduling in cloud computing.

CART- A Statistical Model for Predicting QoE using Machine Learning in Smartphones

The proliferation of fast, cheap, and ubiquitous network access, in particular on mobile devices, has significantly changed the way user’s access online benefits on an everyday premise. Alongside the expanded accessibility of a dependably on Internet, new advancements, for example, LTE have empowered the utilization of a wide range of administrations, with stringent necessities regarding system execution and limit requests. We consider different QoE appraisal models in view of administered machine learning strategies, which are proficient to foresee the QoE experienced by the end client of well-known cell phone applications (e.g., YouTube and Face book), utilizing as info the inactive in-gadget estimations. In this extraordinary issue, we investigate the connection between the Quality of Service (QoS) that administrators screen and oversee and the Quality of Experience (QoE) that the clients really get. Utilizing a rich QoE dataset got from field trials in operational cell systems, we benchmark the execution of various machine learning based indicators, and build a choice tree based model which is able to foresee the per-client general understanding and administration worthiness with a win rate of 91% and 98% separately. To the best of our knowledge, this is the initial proposal using end-user, in-device passive measurements and machine learning models to predict the QoE of smartphone users in operational cellular networks.

Urban Land-Use Classification From Photographs

Land-use (LU) classification of urban areas is conventionally achieved via field survey or remote sensing technologies, which is labor-intensive and time-consuming. With the wide development of social networks such as microblog and ubiquitous network access, images are captured by residents and tourists. In this letter, we propose a method for an automatic urban LU classification using geotagged images from public venues. Our method identifies the LU type depicted in those images that are extrapolated to the local regions bounded by street blocks. Experiments were conducted with geotagged photographs and Open Street Map of an urban area in London, U.K. It was demonstrated that the proposed method achieved overall 76.5% accuracy across five LU types. More importantly, our method demonstrated a greater performance in dealing with a mixture of LU types.

Securing the cloud-assisted smart grid

Rapid elasticity, ubiquitous network access, and highly-reliable services are some of the desirable features of cloud computing that are attractive for building cloud-assisted data-intensive Smart Grid (SG) applications. However, the Distributed Denial-of-Service (DDoS) attacks represent a serious threat to the cloud-assisted SG applications. To mitigate the risk related to the DDoS threat, we propose an SG-relevant Hierarchical Hybrid Cloud-Extension Concept (HHCEC) along with a DDoS attack defense mechanism, termed as Port Hopping Spread Spectrum (PHSS). HHCEC is a cloud-assisted architecture designed to meet scalability and security requirements of the SG applications in the cloud. To prevent transport or application-layer DDoS attacks on HHCEC, PHSS switches the open port of server as a function of time and a secret shared between authorized clients and server, and thus efficiently dropping packets with closed port number. In addition, PHSS spreads the data packets over all the servers versus a single server to provide a robust protection against volume-based DDoS attacks that would affect some of the servers. This packet spreading approach enables PHSS to instantiate replica servers to take over the attacked servers without blocking the whole traffic by utilizing the rapid-elasticity characteristic of the cloud. Moreover, PHSS leverages a shuffling-based containment mechanism in order to quarantine malicious clients in a notably short time. Accordingly, the effect of a DDoS attack based on the compromised secret of the malicious clients is minimized. We evaluate our approach by building a proof-of-concept prototype using Amazon’s EC2 and the PlanetLab test-bed. In a DDoS attack scenario, the proposed approach obtains a significant availability enhancement of > 38% that highlight its efficiency in comparison to existing approaches. The results also indicate negligible overhead for the proposed approach compared to the plain system i.e., no additional latency and less than 0.01% throughput degradation.

Cyber Insurance for Heterogeneous Wireless Networks

Heterogeneous wireless networks (HWNs) composed of densely deployed base stations of different types with various radio access technologies have become a prevailing trend to accommodate ever-increasing traffic demand in enormous volume. Nowadays, users rely heavily on HWNs for ubiquitous network access that contains valuable and critical information such as financial transactions, e-health, and public safety. Cyber risks, representing one of the most significant threats to network security and reliability, are increasing in severity. To address this problem, this article introduces the concept of cyber insurance to transfer the cyber risk (i.e., service outage, as a consequence of cyber risks in HWNs) to a third party insurer. Firstly, a review of the enabling technologies for HWNs and their vulnerabilities to cyber risks is presented. Then, the fundamentals of cyber insurance are introduced, and subsequently, a cyber insurance framework for HWNs is presented. Finally, open issues are discussed and the challenges are highlighted for integrating cyber insurance as a service of next generation HWNs.

Critical Success Factors for Adopting Cloud Computing in the Pharmaceutical Manufacturing Companies

Cloud computing is a model for enabling ubiquitous, easy, and on-demand network access to a shared aggregation of configurable computing sources. Adopting of cloud computing in the pharmaceutical manufacturing is influenced by a group of critical success factors. Therefore, this paper depends on the technological-organizational-environmental (TOE) framework to explore the factors that influence on cloud computing adoption by pharmaceutical industry firms in Jordan through proposing a model for Pharmaceutical Manufacturing Companies. Complexity, compatibility, relative advantage, top management support, firm size, technical readiness, competitive pressure, and trading partner pressure, are the eight critical success factors that have been tested. A survey was utilized to collect data from 16 pharmaceutical manufacturing firms in the capital of Jordan- Amman. Relevant hypotheses were developed and examined by multiple regression analysis. The results of the data analysis generally support the suggested model. In summary, the results of this research have shown that all above-mentioned factors were found to have a significant influence on adoption of cloud computing for the pharmaceutical industry in Jordan. This finding of adoption in cloud computing in the pharmaceutical industry will help firms to take into consideration their information for technologies investments.

Data Integrity Checking with Reliable Data Transfer for Secure Cloud Storage

Currently, an increasing number of data owners prefer to store their data on remote servers due to a number of appealing advantages of cloud storage, say convenience and simplicity, scalability of the service and ubiquitous network access. However, outsourced data's transfer becomes a critical requirement for cloud users because of the emergence of various cloud storage services with different qualities of services. Therefore, the users might not only be anxious about the status of their data on cloud servers but also care whether the data are transferred entirely to the new cloud without corruption and whether the data on original cloud are discarded. To address these challenging issues, in this paper, we propose a novel auditing scheme for cloud storage services characterised by secure data transfer, provable data erasure, high error detection probability, confidential data storage. The proposed scheme can guarantee the integrity of remote data when the data are hosted on cloud servers and are transferred between two clouds, and secure deletion of the transferred data on the original cloud.

A Novel Utility Based Resource Management Scheme in Vehicular Social Edge Computing

Vehicular network aims at providing intelligent transportation and ubiquitous network access. Edge computing is able to reduce the consumption of core network bandwidth and serving latency by processing the generated data at the network edge, and social network is able to provide precise services by analyzing user’s personal behaviors. In this paper, we propose a new network system referred to as vehicular social edge computing (VSEC) that inherits the advantages of both edge computing and social network. VSEC is capable of improving the drivers’ quality of experience while enhancing the service providers’ quality of service. In order to further improve the performance of VSEC, the network utility is modeled and maximized by optimally managing the available network resources via two steps. First, the total processing time is minimized to achieve the optimal payment of the user to each edge device for each kind of the required resource. Second, a utility model is proposed, and the available resources are optimally allocated based on the results from the first step. The two optimization problems are solved by the Lagrangian theory, and the closed-form expressions are obtained. Numerical simulations show different capacities in different scenarios, which may provide some useful insights for VSEC design.

Chain-Branch-Leaf: A clustering scheme for vehicular networks using only V2V communications

The development of vehicular networks leads to a plethora of new applications that are already becoming essential to the drivers and to cooperative vehicles. One important condition to the continuity of these new services is the existence of an ubiquitous network access, which cannot be completely guaranteed. In this context, developing reliable ad hoc vehicle-to-vehicle communications is a good alternative that also becomes mandatory. This work proposes a clustering scheme that combines the information on road configuration, vehicle mobility and link quality in order to build a structure similar to a vehicular network infrastructure, while relying only on the vehicles. This clustering scheme can be integrated into any reactive, proactive, or geographic ad hoc routing protocol in order to optimize the flooding of messages and simplify routing operations. The evaluations realized through simulation show that the proposed clustering scheme allows creating and maintaining a stable backbone during a significant time. Moreover, the simulation results show that the proposed clustering scheme reduces significantly the impact of broadcast traffic flooding in comparison with well-established techniques such as multipoint relaying, to mention few.

Cross layer architecture with integrated MIH in heterogeneous wireless networks

Progress in new radio technologies and raise in users’ demands are motivating the deployment of a wide array of wireless networks, ranging from Wireless Local Area Network (WLAN), to fifth generation (5G). These heterogeneous Radio Access Technologies (RATs) are expected to be integrated together to provide mobile users QoS guarantees. Heterogeneous Wireless Networks (HWNs) provide an opportunity for developers to design efficient framework to satisfy stringent QoS requirement. This integration of different networks results in performance degradation when handovers occur during a mobility event. As a result, the effective mobility management protocols are required to support ubiquitous network access by providing seamless handover. In IEEE 802.21 standard, the framework Media Independent Handover (MIH) is proposed to facilitate handover in heterogeneous networks with measurements and triggers from link layers. This article emphasizes in relationship between the MIH framework and different modules in the MAC layer. In order to guarantee the QoS for different service flows with diverse QoS requirements, we propose to design new cross-layer based designs architecture to provide a combined solution for vertical and horizontal handover based on IEEE 802.21 MIH. We propose new modules in different layers and new primitives to facilitate the communication. Conducted simulations demonstrate the effectiveness of the proposed approaches. We evaluate the proposed architecture using a scheduling algorithm which improves system performance as shown by the results presented of a comparative analysis with the NSA (New Scheduling Algorithm) and EDF (Earliest Deadline First) schemes.

A log aggregation forensic analysis framework for cloud computing environments

Cloud computing has emerged in the past decade to provide wide-ranging computational facilities at cheaper cost. Cloud computing facilitates the sharing of processing units, storage devices and applications. The National Institute of Standards and Technology describes cloud computing as a model for facilitating on-demand ubiquitous network access to a combined pool of computing resources – eg, networks, storage, servers, services and applications. These resources can easily be provisioned and released without the service provider's interaction. Cloud computing is now in widespread use. But it does pose a number of security challenges. Muhammad Naeem Ahmed Khan and ShahWali Ullah of the Shaheed Zulfikar Ali Bhutto Institute of Science and Technology propose an analysis model based on aggregating available logs from clients and servers that could help identify and detail suspicious activity on cloud-based systems.

A novel hybrid of Shortest job first and round Robin with dynamic variable quantum time task scheduling technique

Cloud computing is a ubiquitous network access model to a shared pool of configurable computing resources where available resources must be checked and scheduled using an efficient task scheduler to be assigned to clients. Most of the existing task schedulers, did not achieve the required standards and requirements as some of them only concentrated on waiting time or response time reduction or even both neglecting the starved processes at all. In this paper, we propose a novel hybrid task scheduling algorithm named (SRDQ) combining Shortest-Job-First (SJF) and Round Robin (RR) schedulers considering a dynamic variable task quantum. The proposed algorithms mainly relies on two basic keys the first having a dynamic task quantum to balance waiting time between short and long tasks while the second involves splitting the ready queue into two sub-queues, Q1 for the short tasks and the other for the long ones.Assigning tasks to resources from Q1 or Q2 are done mutually two tasks from Q1 and one task from Q2. For evaluation purpose, three different datasets were utilized during the algorithm simulation conducted using CloudSim environment toolkit 3.0.3 against three different scheduling algorithms SJF, RR and Time Slice Priority Based RR (TSPBRR) Experimentations results and tests indicated the superiority of the proposed algorithm over the state of art in reducing waiting time, response time and partially the starvation of long tasks.

Assessing the Determinants of Cloud Computing Services for Utilizing Health Information Systems: A Case Study

Health information systems refer to the utilization of IT-related systems to capture, store, manage, or transmit information related to the health of individuals or the activities within the health sector. Utilizing cloud services in the healthcare sector is a flexible solution to improve the performance of an organization as it can provide numerous features such as self-service, ubiquitous network access, resource pooling, rapid elasticity, and pay-per-use pattern. A preliminary study was conducted in the Iraqi public healthcare sector to obtain preliminary data acquisition about the current situation of IT and to determine the key factors associated with the utilization of cloud computing to foster current health information systems. During the study, a total of 30 technicians and physicians from four hospitals in Iraq were invited for interview in which the researcher directed questions in a semi-structured form. The findings of the investigation concluded the key determinant factors; these include factors related to the environmental structure such as software, hardware, cost, network, and training. Other factors that were found related to the system such as compatibility, complexity, data security and privacy. These two aspects were found to influence personal factors related to the behavioural control and confirmation to utilize cloud computing services in this sector.

Privacy preserving model: a new scheme for auditing cloud stakeholders

The Cloud computing paradigm provides numerous attractive services to customers such as the provision of the on-demand self-service, usage-based pricing, ubiquitous network access, transference of risk, and location independent resource sharing. However, the security of cloud computing, especially its data privacy, is a highly challengeable task. To address the data privacy issues, several mechanisms have been proposed that use the third party auditor (TPA) to ensure the integrity of outsourced data for the satisfaction of cloud users (CUs). However, the role of the TPA could be the potential security threat itself and can create new security vulnerabilities for the customer’s data. Moreover, the cloud service providers (CSPs) and the CUs could also be the adversaries while deteriorating the stored private data. As a result, the objective of this research is twofold. Our first research goal is to analyze the data privacy-preserving issues by identifying unique privacy requirements and presenting a supportable solution that eliminates the possible threats towards data privacy. Our second research goal is to develop the privacy-preserving model (PPM) to audit all the stakeholders in order to provide a relatively secure cloud computing environment. Specifically, the proposed model ensures the quality of service (QoS) of cloud services and detects potential malicious insiders in CSPs and TPAs. Furthermore, our proposed model provides a methodology to audit a TPA for minimizing any potential insider threats. In addition, CUs can use the proposed model to periodically audit the CSPs using the TPA to ensure the integrity of the outsourced data. For demonstrating and validating the performance, the proposed PPM is programmed in C++ and tested on GreenCloud with NS2 by applying merging processes. The experimental results help to identify the effectiveness, operational efficiency, and reliability of the CSPs. In addition, the results demonstrate the successful rate of handling the negative role of the TPA and determining the TPA’s malicious insider detection capabilities.

Deterministic Time Markov Chain Modelling of Simultaneous Multipath Transmission Schemes

The increase in the availability of multimode devices for ubiquitous network access and the need for larger bandwidth have created a thrust for the utilization of simultaneous network connections. Unfortunately, the standard transport layer protocols such as the transmission control protocol and user datagram protocol have structural constraints. As a result, an Internet application can use only one interface at a time. The stream control transmission protocol (SCTP) provides support for concurrent multipath transfer (SCTP-CMT). In this paper, we present the mathematical modeling of simultaneous multipath transmission (SMT) schemes using the deterministic time Markov chain (DTMC) model. In this DTMC model, receiver buffer size is used for the first time to estimate the sending data rate. The DTMC model of SMT schemes are compared with the SCTP-CMT using probability-based packet dropped scenarios. DTMC modeling is used to mathematically verify simulation results of SMT Schemes i.e., modified fast retransmit (SMT-MFR) and adaptive modified fast retransmit (SMT-AMFR). The analytical model results revealed that SMT-MFR outperformed SCTP-CMT by 8.54% gain in average throughput. SMT-AMFR outperformed the SCTP-CMT and SMT-MFR by 19.65% and 11.15% gain in average throughput, respectively.