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Companies leverage plenty of monitoring tools collecting performance metrics of Telecom BSS to assure it is in good status. The influence of the system failure is variance, depending on the length of time to finish the system reparation. The metrics collected by monitoring tools may have the indication of the system failure, and the maintainers have chances to foresee a system failure from those metrics...
This paper proposes a scalable and efficient cacheupdate technique to improve the performance of in-memorycluster computing in Spark, a popular open-source system forbig data computing. Although the memory cache speeds up dataprocessing in Spark, its data immutability constraint requiresreloading the whole RDD when part of its data is updated. Suchconstraint makes the RDD update inefficient. To address...
In this paper we describe a scheduling framework that allocates resources to both batch jobs and interactive jobs simultaneously in a private cloud with a static amount of resources. In the system, every job has an individual service level agreement (SLA), and violating the SLA incurs penalty. We propose a model to formally quantify the SLA violation penalty of both batch and interactive jobs. The...
Many enterprises or institutes are building private clouds within their own data centers. Data centers may have different batches of physical machines due to annual upgrades, but the number of machines is fixed most of the time. Consequently it is crucial to schedule jobs with different resource requirements and characteristics to meet different job timing constraints, in such heterogeneous yet most...
Growing real-time services require discovering transient customer needs in CDRs. In this paper, we propose a CDR analytics system architecture for event-based analytics processing in real time. This system is expected to allow marketing staff to inject analytics-based rules to trigger marketing campaigns. We also propose two implementations which are based on off-the-shelf computing tools.
Call Detail Record or Charging Data Record (CDR) processing is a computation-intensive task, which is traditionally handled by costly high-performance machines. If extra computing resources are not allocated beforehand, it is fragile to handle peak or urgent events. Cloud computing, which offers elastic computing resources, can cure this problem. In this paper, we investigated several Cloud scheduling...
In recent years, cloud computing is the most popular topic on the IT industry. The underlying virtualization technologies, that make cloud computing possible, also get more and more attention. Gradually, companies move their services to the virtual host. These services include: desktop virtualization, application virtualization and database virtualization etc. Among these services, database virtualization...
With the emerging of digital convergence, lots of communication services are generated, and the quantity of data grows rapidly. We face the scalability issue to deal with call data records (CDRs) and so are the other telecom companies. This research uses police CDR query as an example with an intension to increase system execution efficiency and scalability and to reduce total cost by applying cloud...
Recently, there has been growing interest in understanding information cascading phenomenon on popular social networks such as Face book, Twitter and Plurk. The numerous diffusion events indicate huge governmental and commercial potential. People have proposed several diffusion and cascading models based on certain assumption, but until now we do not know which one is better in predicting information...
System performance monitoring accumulates and analyzes performance information to detect and evaluate anomaly performance behavior. Recent advances in Internet based services have led to an increasing variety and complexity. Abnormal service operations adversely impact other services, making it extremely difficult to identify and resolve anomaly performance behavior. This work describes a novel multilayered...
This work presents an unsupervised snippet-based sentiment classification method for Chinese unknown sentiment phrases, which is also applicable to other languages theoretically. Unlike existing Semantic Orientation (SO) methods, our proposed method does not require any Reference Word Pairs (RWPs) for predicting the sentiments of phrases. The results of preliminary experiments show that our proposed...
Accelerated growth of the Internet has enabled users worldwide to share their feelings and experiences. User-generated content (UGC) websites are the most abundant sources of user reviews. Accurately identifying sentiment phrases is essential to understand the expressed opinions in user reviews. To achieve this, part-of-speech (POS) patterns of phrases are useful. However, previous studies for Chinese...
Consumer reviews are dominating consumer purchase decisions, and restaurant (cuisine) reviews are one of the most popular genres of consumer reviews. In contrast to traditional named entity recognition (NER) targets, cuisine names are promising targets that were neglected in previous studies. This study proposes a novel cuisine name extraction algorithm, which can extract cuisine names from restaurant...
On-the-go consumers require dynamic information, particularly "word of mouth, " to make better purchase decisions. A popular genre of mobile map services is travel/cuisine, which is a popular topic for bloggers as well. This study attempts to generate local cuisine hotspot maps through blog content mining. The main obstacle in doing this involves recognizing and extracting restaurants and...
Democratic in nature, the Blogosphere allows individuals to accumulate a tremendous amount of personal knowledge, share experiences, and express opinions. Based on blog contents and social-referral data, blog semantic analysis can identify individual expertise and an appropriate social network, thus obtaining word-of-mouth reviews of certain products or services. Effectively utilizing this opinion...
As GPS devices show a great tendency to be popular, location based services such like instant POI finding become more and more important. On-the-go consumers require dynamic information, particularly ldquoword of mouthrdquo, to make better purchase decisions. To improve user experience on mobile POI finding in unfamiliar area, this study proposes a brand-new POI database comprising information extracted...
A blog has the potential to change the way we perceive information and make friends. Using the value, semantic, and social model of the blogger, this work analyzes the user interfaces and user profile for a proactive recommendation. Retrieving the personal value inclination, article topic semantic, and interactive social network of the bloggers, this study has tried to step toward a blog recommendation...
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