The Internet of Things vision: Key features, applications and open issues

Historically, most demographic data for states and substate areas were collected from the long version of the decennial census questionnaire. A “snapshot” of the characteristics of the population on the April 1 census date was available once every 10 years. The long form of the decennial census has been replaced by the American Community Survey (ACS) that has been conducted on an ongoing basis for the entire country since 2005. Instead of a snapshot in which all of the data are gathered at one time, the ACS aggregates data collected over time, making the results more difficult to interpret. However, the ACS data are updated annually.

A practical guide to the American Community Survey (3-year estimates)

The unabated flurry of research activities to augment various mobile devices by leveraging heterogeneous cloud resources has created a new research domain called Mobile Cloud Computing (MCC). In the core of such a non-uniform environment, facilitating interoperability, portability, and integration among heterogeneous platforms is nontrivial. Building such facilitators in MCC requires investigations to understand heterogeneity and its challenges over the roots. Although there are many research studies in mobile computing and cloud computing, convergence of these two areas grants further academic efforts towards flourishing MCC. In this paper, we define MCC, explain its major challenges, discuss heterogeneity in convergent computing (i.e. mobile computing and cloud computing) and networking (wired and wireless networks), and divide it into two dimensions, namely vertical and horizontal. Heterogeneity roots are analyzed and taxonomized as hardware, platform, feature, API, and network. Multidimensional heterogeneity in MCC results in application and code fragmentation problems that impede development of cross-platform mobile applications which is mathematically described. The impacts of heterogeneity in MCC are investigated, related opportunities and challenges are identified, and predominant heterogeneity handling approaches like virtualization, middleware, and service oriented architecture (SOA) are discussed. We outline open issues that help in identifying new research directions in MCC.

Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges

Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable ground from academia and industry. CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive mobile applications. Augmented mobile devices envision to perform extensive computations and to store big data beyond their intrinsic capabilities with least footprint and vulnerability. Researchers utilize varied cloud-based computing resources (e.g., distant clouds and nearby mobile nodes) to meet various computing requirements of mobile users. However, employing cloud-based computing resources is not a straightforward panacea. Comprehending critical factors (e.g., current state of mobile client and remote resources) that impact on augmentation process and optimum selection of cloud-based resource types are some challenges that hinder CMA adaptability. This paper comprehensively surveys the mobile augmentation domain and presents taxonomy of CMA approaches. The objectives of this study is to highlight the effects of remote resources on the quality and reliability of augmentation processes and discuss the challenges and opportunities of employing varied cloud-based resources in augmenting mobile devices. We present augmentation definition, motivation, and taxonomy of augmentation types, including traditional and cloud-based. We critically analyze the state-of-the-art CMA approaches and classify them into four groups of distant fixed, proximate fixed, proximate mobile, and hybrid to present a taxonomy. Vital decision making and performance limitation factors that influence on the adoption of CMA approaches are introduced and an exemplary decision making flowchart for future CMA approaches are presented. Impacts of CMA approaches on mobile computing is discussed and open challenges are presented as the future research directions.

Cloud-Based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges

In the fifth-generation (5G) mobile communication system, various service requirements of different communication environments are expected to be satisfied. As a new evolution network structure, heterogeneous network (HetNet) has been studied in recent years. Compared with homogeneous networks, HetNets can increase the opportunity in the spatial resource reuse and improve users’ quality of service by developing small cells into the coverage of macrocells. Since there is mutual interference among different users and the limited spectrum resource in HetNets, however, efficient resource allocation (RA) algorithms are vitally important to reduce the mutual interference and achieve spectrum sharing. In this article, we provide a comprehensive survey on RA in HetNets for 5G communications. Specifically, we first introduce the definition and different network scenarios of HetNets. Second, RA models are discussed. Then, we present a classification to analyze current RA algorithms for the existing works. Finally, some challenging issues and future research trends are discussed. Accordingly, we provide two potential structures for 6G communications to solve the RA problems of the next-generation HetNets, such as a learning-based RA structure and a control-based RA structure. The goal of this article is to provide important information on HetNets, which could be used to guide the development of more efficient techniques in this research area.

/pdf/a-survey-on-resource-allocation-for-5g-heterogeneous-4gmdtz8zbn.pdf

A Survey on Resource Allocation for 5G Heterogeneous Networks: Current Research, Future Trends, and Challenges

https://titania.ctie.monash.edu/papers/vhd-survey-comp-networks-2010.pdf

A survey of vertical handover decision algorithms in Fourth Generation heterogeneous wireless networks

CSin3 is a cohort-based, three-year computer science bachelor's degree program that has increased graduation rates of traditionally underrepresented computer science students. A collaborative effort between a community college and a public university, CSin3 provides a clear pathway for upward socio-economic mobility into the high-paying technology industry. CSin3 students are 90% from traditionally underrepresented groups, 80% first-generation, 32% female, and have a three-year graduation rate of 71%, compared to a 22% four-year graduation rate for traditional computer science students. Upon graduation, CSin3 students score similarly on a standardized exam of computer science knowledge as compared to traditional students who graduate in 4 years or more. The first graduates had a job placement rate of 78% within two months of graduation, including positions at large technology companies like Apple, Salesforce, and Uber. By implementing a cohort-based learning community, a pre-defined course pathway, just-in-time academic and administrative support, comprehensive financial aid, and a focus on 21st century skills, the CSin3 program has demonstrated promising results in addressing the capacity, cost, quality, and diversity challenges present in the technology industry.

https://dl.acm.org/doi/pdf/10.1145/3159450.3159551

Upward Mobility for Underrepresented Students: A Model for a Cohort-Based Bachelor's Degree in Computer Science

An integrated software tool using the open source applications iPerf and ping was developed to measure broadband wireless performance in California. Statistics on TCP download/upload throughput, latency, UDP packet jitter and loss, network type, and network provider were recorded. The software can be installed on a Window-based laptop and Android-based smart phone. An analysis script was also developed to analyze measurement results on the database server. Using the software, testers conducted field test at 1,200 different locations in California, and the test result will be accessible to the general public using a viewer application. In addition, selected locations ran Glasnost, a traffic shaping detection tool, to determine if network providers altered performance of flows based on type or port number.

Wireless Broadband Measurement in California

https://dl.acm.org/doi/pdf/10.1145/3210555

Upward mobility for underrepresented students: a model for a cohort-based bachelor's degree in computer science

A variety of network deployments in disaster recovery, fire fighting and military scenarios create networks that do not form a connected network all the time. In such scenarios, paths between a source and destination may be created over time when nodes encounter each other due to node mobility. Many routing algorithms that can route messages in such delay-tolerant networking (DTN) settings have been proposed. Currently, these protocols do not differentiate between the messages that are being routed through the network treating all messages equally. But, there are DTN scenarios, in particular in military situations, where it is critical that messages are differentiated based on their importance to the task being supported. In this paper, we propose extensions to two popular DTN routing protocols, Epidemic and PROPHET, to implement such message prioritization. We implemented the proposed extensions in ONE (Opportunistic Network Emulator) and studied the performance of these extensions. Results from our simulation analysis demonstrate that it is possible to implement message prioritization in non-deterministic delay tolerant networks and provide us with insights into configuring message prioritization in DTN. In particular, the importance of selecting optimal queue lengths at each node to mitigate congestion in such networks.

Sathya Narayanan

Papers

A survey of vertical handover decision algorithms in Fourth Generation heterogeneous wireless networks

Upward Mobility for Underrepresented Students: A Model for a Cohort-Based Bachelor's Degree in Computer Science

Wireless Broadband Measurement in California

Upward mobility for underrepresented students: a model for a cohort-based bachelor's degree in computer science

Performance analysis of message prioritization in delay tolerant networks