An analysis was made of the indications and outcome of immediate reconstruction of the anal sphincter after fistulectomy in the management of a selected group of patients who were at risk of post-operative incontinence. A total of 31 patients underwent surgery, with 25 high trans-sphincteric fistulas (80.6%), four low trans-sphincteric fistulas (12.9%), and two suprasphincteric fistulas (6.5%). The median post-operative stay was 7.0 days, with a median follow up of 24.0 months. We describe one case (3.2%) of post-operative infection and dehiscence of the muscle suture. The fistula recurred in three patients (9.7%). At the end of follow up of 25 patients with full preoperative continence, five patients (20.0%) presented with perianal soiling and one (4.0%) had incontinence to flatus. Sphincter reconstruction after fistulectomy constitutes a management option that should be considered in the treatment of certain fistulas. It allows both rapid recovery and the preservation of anal function.

Parallelism in applications that act on a stream of input data can be exploited with two different approaches, spatial and temporal. In this paper we propose a new task mapping algorithm, called EXPERT, to exploit temporal parallelism efficiently when the streaming application is running in a pipeline fashion. We compare the performance of spatial and temporal approaches, in terms of latency and throughput for a video compression application. The results show that the pipeline execution with the task assignment provided by EXPERT algorithm, significantly overcomes spatial parallelism. Additionally, this temporal parallelism presents better scalability results when the dimension of the problem is augmented.

Nowadays, the use of Radio Frequency Identification (RFID) systems in industry and stores has increased. Nevertheless, some of these systems present privacy problems that may discourage potential users. Hence, high confidence and efficient privacy protocols are urgently needed. Previous studies in the literature proposed schemes that are proven to be secure, but they have scalability problems. A feasible and scalable protocol to guarantee privacy is presented in this paper. The proposed protocol uses elliptic curve cryptography combined with a zero knowledge-based authentication scheme. An analysis to prove the system secure, and even forward secure is also provided.

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MMORPG (Massively Multiplayer Online Role Playing Games) is the most popular genre among network gamers, and now attract millions of users, who play simultaneously in an evolving virtual world. This huge number of concurrent players requires the availability of high performance computation servers. Additionally, gaming aware distribution mechanisms are needed to distribute game instances among servers to avoid load imbalances that affect performance negatively. In this work, we tackle the problem of game distribution and scalability by means of a hybrid Client-Server/P2P architecture that can scale dynamically according to the demand. To manage peak loads that occur during the game, we distribute game computation across the system according to the behavior of MMORPGs. We distinguish between the computation associated with the Main Game, that affects all players, and the computation of Auxiliary Games that affects only a few players and acts in isolation from the execution of the Main Game. Taking this distinction into account, we propose a mechanism that is focused in the distribution of Auxiliary Games, as an entity, across the pool of servers and peers of the underlying hybrid architecture. We evaluate the performance of the balancing mechanism taking the criteria of latency and reliability into account, and we compare the effectiveness of the mechanism with a classic approach that applies load balancing to individually players in a Client-Server system. We show that the balancing mechanism based on the latency criteria provides lower latency Appl (2016Appl ( ) 75:2005Appl ( -2029 than the classical proposal, while in relation to reliability, we obtain a failure probability of under 0.9 % in the worst case, which is amply compensated by the scalability provided by the use of the P2P area.

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There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when executing them. In this paper we propose a new task replication methodology for optimizing throughput for an image processing application in the field of medicine. The results show that by applying the proposed methodology we are able to achieve the desired throughput in all cases, in such a way that the input frames can be processed at any given rate.