The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Mobile applications are usually developed in a native way, using languages and APIs specific for a given platform, hindering the portability. As an alternative, web technologies as JavaScript and PHP have been employed enabling a same implementation to be executed in different mobile platforms without any recompilation or recoding process. This paper compares the efficiency of Android applications...
Given mobile devices ubiquity and capabilities, some researchers now consider them as resource providers of distributed environments called mobile Grids for running resource intensive software. Therefore, job scheduling has to deal with device singularities, such as energy constraints, mobility and unstable connectivity. Many existing schedulers consider at least one of these aspects, but their applicability...
As communication and sensing capabilities of mobile devices increase, mobile applications are becoming increasingly complex. The ability of computation offloading, which is one of the main features of mobile edge computing gains relevance as a technique to improve the battery lifetime of mobile devices and increase the performance of applications. In this paper, we describe the offloading system model...
Mobile and wearable devices are nowadays the de facto personal computers, while desktop computers are becoming less popular. Therefore, it is important for companies to deliver efficient mobile applications. As an example, Google has published a set of best practices to optimize the performance of Android applications. However, these guidelines fall short to address energy consumption. As mobile software...
Mobile Ad Hoc Cloud (MAC) enables the use of a multitude of proximate resource-rich mobile devices to provide computational services in the vicinity. However, inattention to mobile device resources and operational heterogeneity-measuring parameters, such as CPU speed, number of cores, and workload, when allocating task in MAC, causes inefficient resource utilization that prolongs task execution time...
Due to the ever growing mobile broadband data traffic over the cellular networks, the small cell deployment is seen as a promising solution for the network operators to increase their network capacity at low cost. This in turn would lead to an increase number of handovers (HOs) for the mobile users, which could affect the device power consumption. In this context, this paper investigates the impact...
The "free app" distribution model has been extremely popular with end users and developers. Developers use mobile ads to generate revenue and cover the cost of developing these free apps. Although the apps are ostensibly free, they in fact do come with hidden costs. Our study of 21 real world Android apps shows that the use of ads leads to mobile apps that consume significantly more network...
The need for increased performance of mobile device directly conflicts with the desire for longer battery life. Offloading computation to resourceful servers is an effective method to reduce energy consumption and enhance performance for mobile applications. Android provides mechanisms for creating mobile applications but lacks a native scheduling system for determining where code should be executed...
It is common practice for mobile devices to offload computationally heavy tasks off to a cloud, which has greater computational resources. In this paper, we consider an environment in which computational offloading is made among collaborative mobile devices.We call such an environment a mobile device cloud (MDC). We highlight the gain in computation time and energy consumption that can be achieved...
Mobile users always require an excellent user experience which is the top challenge faced by today's mobile device designers and producers. Mobile devices are battery constrained, thus developing energy-saving techniques to extend the battery life is critical in terms of the user experience. Since the discrepancy between the device energy and battery energy consumption is becoming large when the battery...
Improving performance of a mobile application by offloading its computation onto a cloudlet has become a prevalent paradigm. Among mobile applications, the category of interactive data-streaming applications is emerging while having not yet received sufficient attention. During computation offloading, the performance of this category of applications (including response time and throughput) depends...
Computation offloading is one of the approaches used for increasing application efficiency and decreasing energy consumption on consumer devices, an issue especially important for mobile appliances. While some such systems have been previously designed, very little research has been directed towards offloading code from web applications, an alternative to native solutions recently gaining in popularity...
In this paper we consider a system that uses computation offloading, where an infrastructure-based cloud server executes jobs on behalf of a set of mobile devices. In this type of system, mobile job completion times include the latency needed for uploading to the cloud server. Since the processed jobs are subject to hard deadline constraints, this can introduce energy unfairness where mobile devices...
We introduce a user–centric approach to forward cached web objects from one peripheral device to a user’s main mobile device, such as a smartphone. Our approach allows for a reduction in data that is required to be downloaded using the cellular interface when users are mobile. In turn, this reduces the energy consumption and potential latency requiring only basic algorithms that can be implemented...
With the increasing availability of mobile applications, the usage of mobile devices, especially smart phones and tablets, has become popular nowadays. However, mobile devices are limited in battery, memory, storage, and processing capabilities. These constraints prevent mobile devices from widely running all kinds of rich mobile applications. Computation offloading is believed to be a potential solution...
The effectiveness and influence rate of cloud computing services in devices with limited power and computation resources (e.g. mobile devices) has been considered by many researchers and has led to many performed researches and IT products for these devices. One of the most challenging issues during migration of applications and processes to clouds is the rate energy consumption and time management...
Mobile devices provide computing power for running software applications as well as cell phone functionality. However, they could not host complex software applications, mainly due to their limited resources. This limitation can well be remedied by architectural design. We provide taxonomy with six different architectural patterns; standalone, full offloading, partial offloading, SaaS-based, CaaS-based,...
Taking the characteristics of mobile devices and the demands for graphics rendering into account, this paper gives a set of definitions of attributes to express the performance of mobile terminals and algorithm performance. And then, according to the relationship of these attributes, a point-based rendering architecture for mobile devices is proposed. It includes pre-processing simplification, data...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.