To align with sustainability goals, such as Net Zero Emissions, serverless providers must incorporate energy considerations into their resource management models. In edge computing environments, where resources are scarce and latency requirements are stringent, serverless frameworks like OpenFaaS and OpenWhisk commonly rely on Kubernetes for function allocation on edge nodes. However, these frameworks often overlook energy consumption as a critical decision factor, which leads to increased energy costs and higher operational expenses (OPEX). To address this gap, we introduce Go-Green-Go-Cheap (3GC) approach-a deadline-aware and cost-effective resource allocation strategy tailored for serverless service providers to minimize energy and execution costs. 3GC enables real-time resource allocation and leverages the per-core Dynamic Voltage and Frequency Scaling (DVFS) feature to finely tune the balance between execution time and energy consumption. Our evaluation demonstrates that 3GC surpasses existing allocation techniques, achieving cost savings of 39.35% up to 69.43%, while consistently meeting function latency requirements.

Intrusion Detection Systems (IDS) are critical for securing modern networks and systems; however, traditional IDS approaches often rely solely on network traffic or host-level data, limiting their ability to detect sophisticated threats such as AI-driven, zero-day, and polymorphic attacks. This limitation is even more pronounced in highly dynamic environments, such as cloud-based and containerized architectures, where the potential of leveraging rich contextual information remains underexplored. To address this gap, we propose a novel Multidimensional Intrusion Detection System (MIDS) approach that integrates multiple data dimensions, including network and container features, to enhance threat detection in containerized environments. By combining these dimensions, MIDS provides a holistic view of the cluster, enabling more comprehensive threat analysis and improved detection accuracy. We introduce a new data merging technique that unifies network flows with container metrics to facilitate multidimensional analysis. Due to the lack of existing datasets containing such heterogeneous data, we generated two MIDS datasets by simulating prevalent attacks on two well-known containerized applications deployed on Kubernetes (K8s): one using the Damn Vulnerable Web Application (DVWA) and the other using Google's Bank of Anthos (BoA). These simulations included Denial of Service (DoS), brute force, and SQL injection attacks. We evaluated state-of-the-art machine learning (ML) algorithms on these datasets, including SVM, XGBoost, and DNN. The experimental results demonstrate that using MIDS enables ML algorithms to achieve up to 8.69 % and 30.07 % higher F1 scores compared to using only network or container data, respectively. Feature analysis highlights the complementary contributions of network and container dimensions, showcasing the effectiveness of the proposed multidimensional approach for intrusion detection in containerized environments.

Orchestration mechanisms play a pivotal role in assisting service providers in deploying their increasingly complex virtual network services seamlessly thanks to Network Function Virtualization (NFV) and Software-defined networking (SDN) technology enablers. Unfortunately, existing state-of-the-art orchestration techniques suffer from non-scalability and time-efficiency aptitude when the services require VNFs to be distributed across cloud and edge environments with complex dimensions. Furthermore, they provide competitive solutions in good execution time only for small-scale scenarios (e.g., in seconds for 50 nodes) but generally require an exorbitant amount of time to converge towards feasible solutions for medium-scale or even large-scale schemes. This paper proposes VAPNIC: an innovative approach that solves the VNF placement and chaining problem with lower algorithmic complexity using a disjoint-set data structure aided divide-and-conquer strategy. Our method's unique design is the non-use of any existing shortest path search algorithms to chain the virtual network functions. To the best of our knowledge, this is the first work that strives to tackle the placement and chaining of the VNFs from a distinctive perspective in the case of medium-and-large scale scenarios with a fast and scalable heuristic that exploits the divide-and-conquer design paradigm based on multi-branched recursion. Experimental results indicate that VAPNIC outperforms existing approaches in acceptance rate, resource utilization, scalability, and time efficiency.

Time-efficient and scalable mechanisms have a significant role in aiding cloud providers to deploy their increasingly complex virtual network services in a seamless manner thanks to Network Function Virtualization (NFV) and Software Defined Networking (SDN) paradigms. Unfortunately, existing state-of-the-art techniques suffer from non-scalability aptitude and often do not converge rapidly towards feasible solutions, although they provide competetive solutions in acceptable execution time for small-scale scenarios.In this paper, we propose RAFALE, a novel approach that formulates the orchestration problem as a graph matching problem and solves it using two exact algorithms. To the best of our knowledge, this is the first work that attempts to tackle the placement and chaining of the VNFs from a different perspective. Experimental results indicate that RAFALE outperforms, in terms of scalability and time-complexity, the well-known VF2 graph matching algorithm and two existing heuristic-based approaches for the placement and chaining of the VNFs.

Time Slotted Channel Hopping (TSCH) is one of the most used MAC mechanisms introduced by the new amendment IEEE 802.15.4e. It combines both slotted access with channel hopping technique to allow multiple communications while exploiting the 16 available channels of 2.4GHz band. The channel hopping mechanism of 802.15.4e considers an interference-free environment and does not specify how to build and manage a schedule for communication purpose. In this paper, we propose a new distributed channel hopping scheme that exploits Latin rectangles to avoid interference and collisions. In essence, the scheduling of links is performed by Latin rectangles where rows are channel offsets and columns are slot offsets. Thus, the frequency of communication is derived using Latin rectangles. Consequently, interference and multi-path fading are mitigated with more reliability and robustness. The efficiency of the proposed scheme has been validated by extensive simulation.