A microservice-based application is composed of a set of small services that run within their own processes and communicate with a lightweight mechanism. Processing the microservices efficiently with minimum processing time and cost, while utilizing the computing resources efficiently, is a challenging task in a cloud environment. To address this challenge, in this paper, we propose a new container-aware

Internet of Things (IoT) devices strive to maximize their utilities and preserve security of IoT system within limited capacity. In effect, these kinds of devices can be resumed to be rational devices toward the view of game theory. Previous utilities inherit the definitions deriving from quintessential games (e.g. prisoner's dilemma game). However, they are criticized for either arbitrary or elaboration

Internet-of-Things (IoT) is massively growing and introducing several benefits that are able to transform the world. Also, cloud computing has become significantly important due to its ability to handle large sets of data. IoT and cloud computing present a stalwart combination that can enrich several analytics and applications. Nevertheless, cloud data security and users privacy can have gaps. Especially

The diverse service requirements coming with the advent of sophisticated applications as well as a large number of connected devices demand for revolutionary changes in the traditional distributed radio access network (RAN). To this end, Cloud-RAN (CRAN) is considered as an important paradigm to enhance the performance of the upcoming fifth generation (5G) and beyond wireless networks in terms of capacity

Object detection models play an essential role in various IoT devices as one of the core components. Scientific experiments have proven that object detection models are vulnerable to adversarial examples. Heretofore, some attack methods against object detection models have been proposed, but the existing attack methods can only attack white-box models or a specific type of black-box models. In this

Synthetic aperture radar (SAR) image target recognition has consistently been a research hotspot in the field of radar image interpretation. Compared with traditional target recognition algorithms, SAR target recognition algorithms based on deep learning offer end-to-end feature learning, which can effectively improve the target recognition rate, making them an important method for radar target recognition

The conceptual approach known as Fog/Edge Computing has recently emerged, aiming to move part of the computing and storage resources from the cloud to the edge of the network. The combination of IoT devices, edge nodes, and the Cloud gives rise to a three-tier Cloud of Things (CoT) architecture. In the complex and dynamic CoT ecosystems, a key issue is how to efficiently and effectively allocate resources

Software Defined Networking (SDN) is a revolutionary paradigm that is maturing along with other network technologies in the next-gen trend. The separation of control and data planes in SDN enables the emergence of novel network features like centralized flow management and network programmability that encourage the introduction of new and enhanced network functions in order to improve prominent network

The End-to-End VPN security has an essential role especially in connecting smart objects in the Internet of Things (IoT) environments. It noted that security is a crucial issue in the End-to-End VPN approach. IPSec/IPv6 and OpenSSL are the most common VPN approaches used separately to secure smart IoT objects in different environments. These approaches have strengths and weaknesses. This paper addresses

Currently, Internet applications running on mobile devices generate a massive amount of data that can be transmitted to a Cloud for processing. However, one fundamental limitation of a Cloud is the connectivity with end devices. Fog Computing overcomes this limitation and supports the requirements of time-sensitive applications by distributing computation, communication, and storage services along

Network function virtualization is an emerging concept that is attracting increasing attention in the industry because it offers high levels of agility and flexibility to the network allowing easier software updates, resource adjustment and scalable changes in the configuration of the services. Network functions traditionally delivered on hardware and purpose-built platforms in legacy networks can

The proliferation of location-based services highlights the need to develop an accurate indoor localization solution. The global navigation satellite system does not deliver good accuracy indoors because of weak signal. One solution is to piggyback Wi-Fi technology, which is widespread in offices and domestic environments. This wireless communication has a promising future, with the possibility to

Future wireless systems are expected to provide a wide range of services to more and more users. Advanced scheduling strategies thus arise not only to perform efficient radio resource management, but also to provide fairness among the users. On the other hand, the users’ perceived quality, i.e., Quality of Experience (QoE), is becoming one of the main drivers within the schedulers design. In this context

Deep learning (DL) is an increasingly important tool for large-scale data analytics and DL workloads are also common in today's production clusters due to the increasing number of deep-learning-driven services (e.g., online search and speech recognition). To handle ever-growing training datasets, it is common to conduct distributed DL (DDL) training to leverage multiple machines in parallel. Training

Due to the prosperity of online videos, caching video content has become an important measure to improve the user experience and alleviate the link burden in the wireless caching networks. However, facing to the perceptual requirements of video users, Scalable Video Coding (SVC) technique has been cumulatively used in wireless caching networks, which can guarantee acceptable video quality. In this

The emerging future generation 5G technology is expected to support service-oriented virtualized networks where different network applications provide unique services. 5G networks have the potential to allow completely different slices to co-exist in a substrate network and satisfy the differentiated requirements of various users. In networks with heterogeneous traffics, operators are required to provide

Web traffic on e-business sites is increasingly dominated by artificial agents (Web bots) which pose a threat to the website security, privacy, and performance. To develop efficient bot detection methods and discover reliable e-customer behavioural patterns, the accurate separation of traffic generated by legitimate users and Web bots is necessary. This paper proposes a machine learning solution to

We investigate the privacy, security, and trust issues of the Android bloatware applications and evaluate the claims regarding their utility and the coverage of the functional needs of different end-user market segments. We analyze 17,179 bloatware applications, extracted from the firmware of 100 Android smartphones manufactured by nine leading original equipment manufacturers (OEMs), and conduct an

By the envision of combing smooth viewing experience with high-efficiency content distribution, dynamic adaptive streaming (DAS) over information-centric networking (ICN) is becoming a promising trend for the future video services. However, optimizations of DAS flow transmission control and rate adaptation need to be revisited for better adopting the ICN with multicast, multi-rate forwarding and decentralized

Compared with individual recommendation, recommending services to a group of users is more complicated because of various users' preference should be considered and introduces new challenging such as fairness, which has never been well studied in current works. In this paper, we propose a novel recommendation scheme called PFGR, which combines a probabilistic model with coalition game strategy, to

The demand of highway lighting system is ubiquitous but its operation contributes to extensive financial cost and concerning environmental implications. For this reason, recent researches have investigated possible solutions to boost the efficiency of the existing lighting system. However, the ultimate guide for green energy enabled smart highway lighting system is still lacking in terms of quality

Unlike the scalar data (such as temperature, pressure and humidity), the vector data (such as image, audio and video) necessitates more stringent Quality of Service (QoS) requirements in terms of bandwidth, delay, reliability and information security. These QoS requirements can be hardly achieved in a proper fashion by using a single channel for wireless communication. However, multichannel methodology

As the Internet of Things (IoT) recently attains tremendous popularity, this promising technology leads to a variety of security challenges. The traditional solutions do not fit the new challenges brought by the IoT ecosystem. Although the development's area of Artificial Immune Systems (AIS) provides an opportunity to improve security issues and create a fertile and exciting environment for further