Scrum of scrums is an approach used to scale the\ud traditional Scrum methodology to fit for the development of\ud complex and large projects. However, scaling the roles of scrum\ud members brought new challenges especially in distributed and\ud large software projects. This paper describes in details the roles\ud of each scrum member in scrum of scrum to propose a solution\ud to use a dedicated product owner for a team and inclusion of\ud sub-backlog. The main goal of the proposed solution is to\ud optimize the role of product owner for distributed large projects.\ud The proposed changes will increase cohesiveness among scrum\ud teams and it will also eliminate duplication of work. Survey is\ud used as a research design to evaluate the proposed solution. The\ud results are found encouraging supporting the proposed solution.\ud It is anticipated that the proposed solution will help the software\ud companies to scale Scrum methodology effectively for large and\ud complex software projects

Recently, Underwater Sensor Networks (UWSNs) have attracted researchers’ attention due to the challenges and the peculiar characteristics of the underwater environment. The initial random deployment of UWSN where sensors are scattered over the area via planes or ships is inefficient, and it doesn’t achieve full coverage nor maintain network connectivity. Moreover, energy efficiency in underwater networks is a crucial issue since nodes utilize battery power as a source of energy and it is difficult and sometimes impossible to change or replenish these batteries. Our contribution in this research is to improve the performance of UWSNs by designing UW-DVFA, an underwater 3-D self-distributed deployment algorithm based on virtual forces. The main target for this work is to stretch the randomly deployed network in the 3-D area in a way that guarantees full area coverage and network connectivity.

The Internet of Underwater Things (IoUT) represents an emerging and innovative field with the potential to revolutionize underwater exploration and monitoring. Despite its promise, IoUT faces significant challenges related to reliability and security, which hinder its development and deployment. A particularly critical issue is the establishment of trustworthy communication networks, necessitating the adaptation and enhancement of existing models from terrestrial and marine systems to address the specific requirements of IoUT. This work explores the problem of dishonest recommendations within trust modelling systems, a critical issue that undermines the integrity of trust modelling in IoUT networks. The unique environmental and operational constraints of IoUT exacerbate the severity of this issue, making current detection methods insufficient. To address this issue, a recommendation evaluation method that leverages both filtering and weighting strategies is proposed to enhance the detection of dishonest recommendations. The model introduces a filtering technique that combines outlier detection with deviation analysis to make initial decisions based on both majority outcomes and personal experiences. Additionally, a belief function is developed to weight received recommendations based on multiple criteria, including freshness, similarity, trustworthiness, and the decay of trust over time. This multifaceted weighting strategy ensures that recommendations are evaluated from different perspectives to capture deceptive acts that exploit the complex nature of IoUT to the advantage of dishonest recommenders. To validate the proposed model, extensive comparative analyses with existing trust evaluation methods are conducted. Through a series of simulations, the efficacy of the model in capturing dishonest recommendation attacks and improving the accuracy rate of detecting more sophisticated attack scenarios is demonstrated. These results highlight the potential of the model to significantly enhance the trustworthiness of IoUT establishments.