As cloud services expand, the need to improve the performance of data center infrastructure becomes more important. High-performance computing, advanced networking solutions, and resource optimization strategies can help data centers maintain the speed and efficiency necessary to provide high-quality cloud services. Running containerized applications is one such optimization strategy, offering benefits such as improved portability, enhanced security, better resource utilization, faster deployment and scaling, and improved integration and interoperability. These benefits can help organizations improve their application deployment and management, enabling them to respond more quickly and effectively to dynamic business needs. Kubernetes is a container orchestration system designed to automate the deployment, scaling, and management of containerized applications. One of its key features is the ability to schedule the deployment and execution of containers across a cluster of nodes using a scheduling algorithm. This algorithm determines the best placement of containers on the available nodes in the cluster. In this paper, we provide a comprehensive review of various scheduling algorithms in the context of Kubernetes. We characterize and group them into four sub-categories: generic scheduling, multi-objective optimization-based scheduling, AI-focused scheduling, and autoscaling enabled scheduling, and identify gaps and issues that require further research.

The Internet of Things (IoT) is an emerging paradigm branded by heterogeneous technologies composed of smart ubiquitous objects that are seamlessly connected to the Internet. These objects are deployed as Low power and Lossy Networks (LLN) to provide innovative services in various application domains such as smart cities, smart health, and smart communities. The LLN is a form of a network where the interconnected devices are highly resource-constrained (i.e., power, memory, and processing) and characterized by high loss rates, low data rates, and instability in the communication links. Additionally, IoT devices produce a massive amount of confidential and security-sensitive data. Various cryptographic-based techniques exist that can effectively cope with security attacks but are not suitable for IoT as they incur high consumption of resources (i.e., memory, storage and processing). One way to address this problem is by offloading the additional security-related operations to a more resourceful entity such as a fog-based node. Generally, fog computing enables security and analysis of latency-sensitive data directly at the network’s edge. This paper proposes a novel Fog Security Service (FSS) to provide end-to-end security at the fog layer for IoT devices using two well-established cryptographic schemes, identity-based encryption, and identity-based signature. The FSS provides security services such as authentication, confidentiality, and non-repudiation. The proposed architecture would be implemented and evaluated in an OPNET simulator using a single network topology with different traffic loads. The FSS performed better when compared with the APaaS and the legacy method.

Fully self-organized mobile ad hoc networks (MANETs) represent complex distributed systems that may also be part of a huge complex system, such as a complex system-of-systems used for crisis management operations. Due to the complex nature of MANETs and its resource constraint nodes, there has always been a need to develop lightweight security solutions. Since MANETs require a unique, distinct, and persistent identity per node in order for their security protocols to be viable, Sybil attacks pose a serious threat to such networks. A Sybil attacker can either create more than one identity on a single physical device in order to launch a coordinated attack on the network or can switch identities in order to weaken the detection process, thereby promoting lack of accountability in the network. In this research, we propose a lightweight scheme to detect the new identities of Sybil attackers without using centralized trusted third party or any extra hardware, such as directional antennae or a geographical positioning system. Through the help of extensive simulations and real-world testbed experiments, we are able to demonstrate that our proposed scheme detects Sybil identities with good accuracy even in the presence of mobility.

The tremendous advancement in embedded systems, miniaturization, and wireless technology had allowed Wireless Body Area Networks (WBAN) to have overwhelming applications in e-healthcare, entertainment, sports/games training, etc. WBAN is a special type of wireless sensor network where bio-sensors are attached or embedded to a single human-body designed to connect various bio-sensors and applications, operate autonomously and observe different vital signs of a human body remotely. Despite its enormous benefits and applications, some of the key challenges in designing heterogeneous WBAN is their energy-efficiency, reliability, and fault-tolerance among the installed bio-sensors. Due to the criticality of services related to WBAN applications, it is imperative to have a high degree of reliability and fault-tolerance, especially in the case of health-care monitoring applications where continuous monitoring of patient’s vital information is required for diagnosis. However, in health-care applications, interference and body fading occur, which affect the communication among nodes and gateway, which reduces the reliability and fault-tolerance of the network. To address these issues, in this paper, we have proposed an energy-efficient fault-tolerant scheme to improve the reliability of WBANs. The proposed scheme adopted the cooperative communication and network coding strategy to minimize channel impairment and body fading effect and hence reduces the ensued faults, bit error rate, and energy consumption. Based on the proposed scheme, a case study was designed for remote Sepsis monitoring. The system identifies tracking indicators using cooperative communication to reduce hospital re-admissions and mortality rates. The proposed scheme performance is also evaluated via extensive simulations using various metrics. From the results obtained, it is evident that the proposed scheme reduces energy consumption, delay, and bit error rate, thereby increasing the throughput and reliability in WBAN.

Internet of Vehicles (IoV) has emerged as an advancement over the traditional Vehicular Ad-hoc Networks (VANETs) towards achieving a more efficient intelligent transportation system that is capable of providing various intelligent services and supporting different applications for the drivers and passengers on roads. In order for the IoV and VANETs environments to be able to offer such beneficial road services, huge amounts of data are generated and exchanged among the different communicated entities in these vehicular networks wirelessly via open channels, which could attract the adversaries and threaten the network with several possible types of security attacks. In this survey, we target the authentication part of the security system while highlighting the efficiency of blockchains in the IoV and VANETs environments. First, a detailed background on IoV and blockchain is provided, followed by a wide range of security requirements, challenges, and possible attacks in vehicular networks. Then, a more focused review is provided on the recent blockchain-based authentication schemes in IoV and VANETs with a detailed comparative study in terms of techniques used, network models, evaluation tools, and attacks counteracted. Lastly, some future challenges for IoV security are discussed that are necessary to be addressed in the upcoming research.