Summary In this paper, a two‐tier model has been developed that includes a Handler and a Bloom filter (HBF). In the first‐tier, the handler detects both the flooding and fake signaling attacks. The Bloom filter, in the second‐tier, prevents both the attacks before reaching the victim. In the existing systems, the packet level features are used which do not perform well for detection and prevention of both the attacks. In this work, flow level features are applied in both tiers. The proposed model is implemented on the innocent Session Initiation Protocol (SIP) server in the VoIP network. The two‐tier model ensures the reliability and trustworthiness between the service provider and the customer. Besides, it also provides billing information along with the exact call duration to a customer who makes a call. The experimental results show that the HBF results in a reduced detection time of 9 seconds with the reduced false positive (FP) of less than 1% and the false negative (FN) of 0.002% and also preserves the voice call quality during media conversation.

Managing the performance of the Session Initiation Protocol (SIP) server under heavy load conditions is a critical task in a Voice over Internet Protocol (VoIP) network. In this paper, a two-tier model is proposed for the security, load mitigation, and distribution issues of the SIP server. In the first tier, the proposed handler segregates and drops the malicious traffic. The second tier provides a uniform load of distribution, using the least session termination time (LSTT) algorithm. Besides, the mean session termination time is minimized by reducing the waiting time of the SIP messages. Efficiency of the LSTT algorithm is evaluated through the experimental test bed by considering with and without a handler. The experimental results establish that the proposed two-tier model improves the throughput and the CPU utilization. It also reduces the response time and error rate while preserving the quality of multimedia session delivery. This two-tier model provides robust security, dynamic load distribution, appropriate server selection, and session synchronization.

In today's world, Cloud Computing (CC) enables the users to access computing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located in remote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and task scheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud is employed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the current research work develops a Cost-Effective Optimal Task Scheduling Model (CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) model is used in the proposed work for hybrid clouds. Moreover, the algorithm works on the basis of multi-intentional task completion process with optimal resource allocation. The model was successfully simulated to validate its effectiveness based on factors such as processing time, make span and efficient utilization of virtual machines. The results infer that the proposed model outperformed the existing works and can be relied in future for real-time applications.

Session Initiation Protocol (SIP) is a signaling protocol emerged with an aim to enhance the IP network capabilities in terms of complex service provision. SIP server scalability with load balancing has a greater concern due to the dramatic increase in SIP service demand. Load balancing of session method (request/response) and security measures optimizes the SIP server to regulate of network traffic in Voice over Internet Protocol (VoIP). Establishing a honeywall prior to the load balancer significantly reduces SIP traffic and drops inbound malicious load. In this paper, we propose Active Least Call in SIP Server (ALC_Server) algorithm fulfills objectives like congestion avoidance, improved response times, throughput, resource utilization, reducing server faults, scalability and protection of SIP call from DoS attacks. From the test bed, the proposed two-tier architecture demonstrates that the ALC_Server method dynamically controls the overload and provides robust security, uniform load distribution for SIP servers.

Abstract-Today's world is an information technology's era in that cloud computing arises as promising and developing technology. In the surroundings of cloud computing the resources are provisioned on the basis of demand, as and when required. A giant number of clients (uses cloud) in computation of cloud, can request a number of services or cloud services at the very same time The users demand to access resources are increasing now-a-days, due to this demand it becomes very hard in cloud for allocation of cloud resources accurately and efficiently to the customers, that should satisfy requirements of customers or users and preserve the SLA (service level agreement). Cloud faces many challenges as it is evolving gradually, one of them is scheduling. Here, we contemplate job scheduling, in accordance to the type, of the mission is and varying situation. To efficiently increase the allocating of resource in cloud, one of the foremost job performed is job scheduling, so to get highest profit. Here, we apply, one among of the effective algorithm, first-in-first-out (FIFO), along with markov process technique to prevent blocking probability.