Sanjay Kumar Bose

With the rapid growth of Internet traffic and new services, demands on access network bandwidth and latency have intensified. Fiber-to-the-Room (FTTR) has emerged as a new architecture for indoor networks, extending fiber directly to users via optical edge gateways. Despite FTTR’s performance benefits, concerns about its equipment’s power consumption have been overlooked. This study investigates FTTR-based home networks, developing models for device power consumption and energy use over time. Results indicate higher power consumption required by FTTR-based networks compared to traditional Wi-Fi networks. To mitigate this, we propose leveraging FTTR’s centralized control for an innovative energy-saving mechanism, enhancing network efficiency and reducing overall energy consumption. Additionally, we explore integrating millimeter-wave technology to further boost energy efficiency through increased transmission capacity.

Today, a microwave-based solution is the one commonly used for wireless backhaul networks as it has high capacity and can be easily deployed. For such a microwave-based wireless backhaul network, a well-designed topology is important for efficient capacity utilization and high-quality mobile services. In an earlier work, we presented an approach for topology planning for microwave-based wireless backhaul networks, where an integer linear programming (ILP) model was formulated and a heuristic algorithm was also developed, subject to various constraints. However, the previous heuristic algorithm may merely lead to local optima, and moreover, only a single set of weight factors was considered for the optimization. This cannot guarantee joint optimization over all the relevant performance aspects. We overcome these drawbacks here by employing the Q-learning technique for this topology planning problem. This consists of (a) re-optimizing an initial topology based on a specific set of weight factors and (b) finding an optimal set of these weight factors. To accelerate the Q-learning process, we also develop a parallel Q-learning system to find the optimal set of weight factors. Simulation results indicate that the Q-learning based approach can jointly optimize multiple system objectives and outperforms our earlier heuristic algorithm. The parallel learning system can also significantly expedite the learning process.

A low capital and operational expense (CAPEX, OPEX) based blockage mitigation solution may be needed to provide uninterrupted connectivity in low-budget indoor millimeter-wave (mmWave) scenarios. For this, several solutions based on dynamic-control-delegation (DCD) at the medium-access-control (MAC) layer have been suggested. However, with rapidly changing network-traffic, increased node-mobility and quickly changing blockage characteristics, most of these techniques may fail to provide adequate network coverage. This paper proposes a scalable and inexpensive solution to provide enhanced mmWave coverage in blockage-prone indoor scenarios. This technique is based on the IEEE 802.15.3c [11] supported simultaneously-operated-piconet (SOP) architecture and operates by dynamically re-structuring the SOP hierarchy to mitigate beam-blockages. To study the impact of multiple influencing factors on the SOP, a Markov decision process (MDP) model is employed which uses a stagecoach inspired dynamic-programming approach to find the ideal SOP-structure. Simulation studies validate the efficacy of this method by comparing it to other suggested solutions.

A Clos network is a classical switching network often used in conventional electrical switches. In a Wavelength Selective Switch (WSS) based Clos all-optical switching network, the wavelength dimension needs to be additionally considered. However, the conventional blocking theory of the Clos network may not be valid in this scenario and it may be necessary to conduct a theoretical study specifically for the WSS-based Clos all-optical switching network. In this paper, we derive the strictly non-blocking conditions for the WSS-based Clos network for the cases where there is no wavelength conversion, partial wavelength conversion, and full wavelength conversion. For the situation where there is service blocking, we also formulate probabilistic analytical models to estimate the blocking performance for the three types of WSS-based Clos networks. The gain of transceiver utilization achieved by the WSS-based Clos network with wavelength conversion is evaluated and compared with that of one without wavelength conversion. We also evaluate the impact of partial wavelength conversion capability on the blocking performance of a WSS-based Clos network.

10-Gbps symmetrical passive optical network (XGS-PON) and Wi-Fi 6 are two key technologies to provide gigabit access for the fifth-generation fixed network (F5G). However, how to integrate XGS-PON and Wi-Fi 6 to meet F5G’s stringent quality of service requirements is still a challenge. In this letter, we propose a cooperative resource scheduling scheme, in which a communication tunnel is established to achieve a low end-to-end (E2E) delay by sharing medium access control information between XGS-PON and Wi-Fi 6. Simulation results show that the proposed scheme can significantly reduce the E2E delay for time-sentinel services by up to 50% without sacrificing the performance of non-time-sensitive services.

By overcoming the server box barrier, resource disaggregation in data centers significantly improves resource utilization, which also provides a more cost-efficient approach for resource upgrade and expansion. The advantages of disaggregation have been explored in earlier research to improve the resource efficiency. This paper investigates the potential benefits of disaggregation from the aspect of reliability, which has not been considered before. Resource disaggregation brings a new failure pattern. For example, in a conventional server, the failure of one type of resource leads to the failure of the entire server, so that other types of resources in the same server also become unavailable. After disaggregating, the failure of different types of resources becomes more isolated, so that other resources are still available. In this paper, we model the reliability of a resource allocation request in a server-based or disaggregated DC based on whether the request is allocated with only working resources, or also provisioned with backup. We then consider a resource allocation problem with the objective of maximizing the number of requests accepted with guaranteed reliability. We provide an integer linear programming and a heuristic approach for this. Numerical studies demonstrate that resource disaggregation is possible to improve service reliability.

The ultra-low-loss optical fibers becoming available now offer large effective areas with much better transmission performance than conventional standard single-mode fibers (SSMFs). However, how low the attenuation should be and how large the effective area has to be to benefit the transmission performance of a fiber-optic system have been open questions until now. In the context of an elastic optical network (EON), this paper evaluates for the first time the extent to which both fiber attenuation and effective area impact the network capacity. We first present an optical signal-to-noise ratio (OSNR) model to evaluate the performance of a lightpath considering various optical transmission impairments. We also propose different service-provisioning approaches based on this OSNR model. Simulation studies show that a spectrum-dependent provisioning scheme that considers different levels of cross-channel interference (XCI) requires minimum spectrum resources when provisioning incremental demands, and a margin-reservation scheme that considers different alternate routes shows the lowest bandwidth blocking probability (BBP) when provisioning dynamic lightpath demands. We also estimate optimal launch powers needed by lightpaths for different fiber attenuations and effective areas. Under different launch powers, it is found that lowering fiber attenuation and increasing fiber effective area demonstrate saturation in performance improvement, i.e., initially decreasing fiber attenuation and increasing effective area can significantly improve the network service provisioning performance, but the improvement is much less when the fiber attenuation and effective area are lower than 0.165 dB/km and greater than 110 μm ² , respectively. This implies that it is not necessary to fabricate a fiber with extremely low attenuation and large effective area for the best cost-to-performance ratio.

The increasing popularity of cloud computing would require Data Centers (DCs) to be scaled up rapidly, as needed, to provide adequate computing and storage infrastructure with rapidly growing demands. Since energy costs would be crucially important for these DCs, various approaches have been proposed to operate them efficiently. Virtual data centers (VDCs) are a promising approach for this as they can efficiently provide computing and storage resources to users over a shared physical infrastructure. In the context of VDC services, this paper focuses on improving the energy efficiency of DCs by applying a Dynamic Frequency Scaling (DFS) mechanism to provision VDC services. Specifically, the frequencies applied in each hardware are adaptively adjusted as per the given service requirements. This is done to minimize the overall energy consumption in the DC hardware when embedding a specific VDC. To the best of our knowledge, this is the first work that incorporates this DFS mechanism in the VDC provisioning problem. To minimize the overall energy consumption, we develop both an integer linear programming (ILP) optimization model and efficient heuristic algorithms. Extensive simulations are conducted to show that incorporating the DFS mechanism in VDC service provisioning significantly improves the energy efficiency of a DC when compared with a scheme where this mechanism is not applied. The proposed heuristic algorithms are also efficient and perform almost as well as the optimum ILP model.

The rapidly evolving scenario around cellular networks, Internet of Things (IoT), and the associated services ecosystem has generated a wide range of expectations for the future networks. However, the unavailability of sufficient bandwidth and severe interference prohibit the existing commercially used radio-frequency (RF) bands from supporting some of these services. In this respect, the millimeter wave (mmWave)-based systems are seen as promising alternatives for supporting various high data rate enhanced mobile broadband (eMBB) services. Nevertheless, the adverse wave propagation characteristics in these bands and the resulting media access control (MAC) layer problems of beam blockage restrict these systems from operating in a reliable manner. Therefore, in this article, we propose a MAC layer-based approach of control delegation to tackle the problem of beam blockage. The mechanism uses policy-based relinquishment of access point (AP) control from the default AP to other AP capable member nodes to improve node visibility and alleviate the blockage scenario without requiring any additional network infrastructure. To account for the dynamic behavior of the network, a discrete-time Markov decision process (MDP)-based model is proposed. It uses a dynamic optimization methodology to accommodate multiple reconfigurable performance metrics, which can then be adjusted to cater to different performance criteria. Using computer simulations, we evaluate the effectiveness of our proposed solution for some alternate static and dynamic control policies. Our simulation results show that our proposed solution can significantly reduce the blockage in a network while satisfying a variety of performance objectives over different classes of indoor IoT scenarios.