In elastic optical networks (EONs), spectrum fragmentation occurs when available spectrum resources become split into small, non-contiguous blocks, resulting in inefficient spectrum usage. Traditional methods, which allocate separate, dedicated partitions for each bandwidth demand type, often lead to an underutilized spectrum. Dedicated partitioning limits available slots per demand type, significantly increasing the likelihood of blocking requests, particularly those with higher bandwidth demands—even if sufficient spectrum slots are free in other partitions. To address this challenge, this paper proposes DGSP, a bandwidth demand grouping and spectrum partitioning scheme designed to reduce connection blocking. DGSP utilizes an integer linear programming (ILP) model to optimally group demands based on their slot requirements and determine equitable partition sizes. Within each partition, spectrum allocation is done using the first-last fit (FLF) policy. Simulation studies conducted on two networks confirm that DGSP effectively reduces the blocking probability, achieving improvements of up to 97.51% compared to conventional dedicated partitioning approaches.

Abstract Recent advancement in hardware and the availability of bandwidth open scope for multichannel communication in underwater wireless sensor networks. Utilizing multiple channels for data and control packets in bursty traffic networks can reduce collisions due to several contending nodes. The paper presents a synchronous reservation-based multichannel ordered contention MAC protocol for deep underwater high data rate bottom monitoring applications to improve the overall network throughput. This protocol is proposed as an enhancement over ordered contention MAC (OCMAC) protocol to deal with bursty traffic by reducing transmission collisions. It does so by enabling nodes to employ multichannel technique along with the scheduling technique of OCMAC. The protocol uses separate channels for channel reservation and data transmission. The throughput performance of the network has been analyzed and validated through simulation. Simulation-based results have shown that MOC-MAC outperforms OCMAC in terms of throughput.

Cloud storage service allows its users to store and share data in a cloud environment. To secure the data from unauthorized entities while sharing, cryptographic mechanisms are used. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is one such mechanism, which has been widely used to achieve fine-grained access control over encrypted data. However, user revocation and keyescrow, in CP-ABE, are still remaining as challenging problems. In this paper, we propose a key-escrow resistant CP-ABE based access control scheme to provide efficient user revocation. The security analysis of the scheme has been done using Information Theory Tools. The security analysis establishes that it is unconditionally secure and provides any-wise revocation capability. Moreover, comparison with the other notable works in the area shows that it outperforms them in terms of computational and communication overheads.