Sistem Informasi Konsumsi Daya Listrik dengan Fitur Map Modelling (Studi Kasus Gedung Fakultas Ilmu Terapan Universitas Telkom)

Universitas Telkom adalah institusi yang giat dalam melaksanakan program Green Campus. Sebagai buktinya, Universitas Telkom menjadi peringkat ke-9 dari pemeringkatan UI Greenmetrics 2017 tingkat Nasional. Namun, dalam penerapannya, terdapat beberapa kelemahan pada kampus ini. Salah satunya adalah belum efisiennya dalam penggunaan energi listrik. Setiap bulan biaya pembayaran listrik berkisar diangka 500 juta Rupiah. Hal ini tergolong cukup besar dalam pemakaian energi listrik. Pada proyek akhir dengan judul Sistem Informasi Konsumsi Daya Listrik dengan Fitur Map Modelling (Studi Kasus Gedung Fakultas Ilmu Terapan Universitas Telkom) ini, berfungsi untuk melakukan pemantauan pada banyakanya daya listrik yang di konsumsi pada gedung Fakultas Ilmu Terapan Universitas Telkom. Sistem informasi yang dibuat, berbasis website yang akan menampilkan hasil monitoring yang telah dikirimkan oleh microcontroller melalui google firebase sebagai penyimpan database dari hasil perhitungan komponen microcontroller yang selanjutnya akan diproses agar mengahasilkan citra berbentuk pemodelan peta dari gedung Fakultas Ilmu Terapan. Setelah didapatkan datanya, maka pemodelan akan memberikan tanda berupa warna, di lantai manakah pengguna listrik terbesar di gedung Fakultas Ilmu Terapan. Dengan sistem informasi ini, diharapkan dapat memberikan kontribusi dalam menurunkan konsumsi listrik di kampus Universitas Telkom, khususnya gedung Fakultas Ilmu Terapan, dan member nilai tambah kepada unit pengelola yaitu Logistik Telkom University berupa kemudahan dalam sistem monitoring dan pengontrolan pemakaian listrik. Kata kunci: Konsumsi Daya Listrik, Website, Monitorin

A Survey of Green Networking Research

Reduction of unnecessary energy consumption is becoming a major concern in wired networking, because of the potential economical benefits and of its expected environmental impact. These issues, usually referred to as "green networking", relate to embedding energy-awareness in the design, in the devices and in the protocols of networks. In this work, we first formulate a more precise definition of the "green" attribute. We furthermore identify a few paradigms that are the key enablers of energy-aware networking research. We then overview the current state of the art and provide a taxonomy of the relevant work, with a special focus on wired networking. At a high level, we identify four branches of green networking research that stem from different observations on the root causes of energy waste, namely (i) Adaptive Link Rate, (ii) Interface proxying, (iii) Energy-aware infrastructures and (iv) Energy-aware applications. In this work, we do not only explore specific proposals pertaining to each of the above branches, but also offer a perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate; Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications. 18 pages, 6 figures, 2 table

Corporate influence and the academic computer science discipline. [4: CMU]

Prosopographical work on the four major centers for computer research in the United States has now been conducted, resulting in big questions about the independence of, so called, computer science

What IS Can Do for Environmental Sustainability: A Report from CAiSE’11 Panel on Green and Sustainable IS

The panel on Green and Sustainable Information Systems at the 21st International Conference on Information Systems Engineering (CAiSE’11), held in London in June 2011, was held to discuss issues in Environmental Sustainability and Information Systems within the Information Systems Engineering research community. This panel report describes the panelists’ views on using information systems for improving sustainability and on improving the energy efficiency of the data centres on which information systems are based. The current topics of research, possible contributions of the IS community, and future directions are discussed

Quality Of Service Trades-offs Between central Data Centers And Nano Data Centers

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2015Thesis (M.Sc.) -- İstanbul Technical University, Instıtute of Science and Technology, 2015Hepimiz farkındayız ki günümüzde teknoloji hızla gelişmektedir ve kişilerin gün geçtikçe yeni teknolojik yapılarla karşı karşılaşmasına sebep olmaktadır. Bulut bilişimö web uygulamalarının geliştirmesi ve zenginleştirilmesinde kullanılan en iyi ve yeni teknolojilerinden birisidir. Son yüzyılda, dünyanın dört bir yanındaki internet kullanıcıların büyük bir kısmı bir veya birden fazla internete bağlı cihaza ve bu cihazlardaki çeşitli programlara sahipler. Bu aplikasyonların vasıtası ile üretilen veri hacminin çok büyük bir seviyede olduğundan dolayı ve bunun yanında düşük kalitede veri yönetimi metotları kullanmak neticesinde servis sunucular yavas¸ veya kesintili çalışabilirler ve bu düşük servis kalitesi müşterilerin memnuniyetini ve müşteri sayısını azaltabilir. ˙Internet tabanlı teslimat oluşturucuları günümüzdeki altyapılarda düs¸ük kalitede olan servislerin en önemli sebeplerinden bir tanesidir. Kullanıcılar herhangi bir servis isteği oluşturduklarında o servis isteği internet üzerinden sunuculara ulas¸ır ve sunucu isteği işledikten sonra ona uygun servisi sağlar. Bu işlem zaman alır ve zaman alıcı olmasından dolayı sunucunun servis sağlamasında gecikmelere neden olur. Biz bu çalışmada isteklerin ve servislerin, kullanıcı ve sunucuya ulaşmaları için daha kısa bir mesafe hareket etmelerini ve böylece servislerin daha kaliteli bir şekilde sunulmalarını amaçlıyoruz. Bunun için veri merkezlerini yerel çevrelere taşımayı ve kullanıcıların daha hızlı ve daha az enerji harcayarak servislere ulaşmalarını hedefliyoruz. Bulut bilişimin kendi içerisinde barındırdığı ve belli düzeyde geliştirilmesi gereken kısımları mevcuttur. Bu çalışmada bulut bilişimin alt yapısında bulunan veri merkezinin performansı değerlendirilmiştir. Veri miktarının büyüklüğü günümüzün bu alanda en büyük sorunlarından bir tanesidir. Veri miktarındaki artış, yönetim boşluğuna sebep olmakla birlikte veri merkezinin güncel konfigürasyounun tüketici memnuniyetini karşılamamasına   neden   olmaktadır.      Bu   sebepten   ötürü   bu   çalışmada güncel veri  merkezi  konfigürasyonlarının  yerine  bir  takım  dag˘ıtılmıs¸  veri  merkezlerinin performansı hizmet kalitesini artırmak amacıyla inceleme yoluna gidilmiştir. Yapılan bu çalışmada JAVA programında yazılan ve CloudSim üzerinde inşa edilmiş olan CloudAnalyst simülatörü kullanılmıştır. Mevcut veri merkezi nano düzeydeki veri merkezlerinin değiştirilmesi yoluna başvurularak yeni düzenin eski sistemle kıyaslanması sağlanmıs¸tır. Değişen veri merkezinin özellikleri ise şu şekilde sıralanabilir: Hafıza kapasitesi, işlem hızı, bant genişliği ve bununla birlikte yerel merkezlerine istek gönderen tüketici sayısındaki değişimdir. Bu çalışmada ayrıca tüketici memnuniyeti etkileyen en önemli iki faktör olması sebebiyle eski sistemin ile geliştirilmiş nano düzeydeki yeni sistemi performans açısından ve sistemlerin  kurulum  maliyetleri   açısından  zamana  bag˘lı  olarak  farklı  grafikler üzerinde gösterilmis¸tir.  Bu grafikler  bu  açıdan  deg˘erlendirildig˘inde  nano  düzeydeki      veri      merkezlerinin    mevcut   sisteme   göre   daha   etkili   çalıs¸tıg˘I gözlemlenmis¸tir.   Sonuç olarak nano düzeyde veri merkezlerinin en iyi hizmet verdig˘i es¸ik deg˘erleri tespit edilmis¸tir. Bu  çalıs¸mada  yapılmıs¸  olanlar,  özünde  Nano  servislerinin  kullanıcılar  için  en iyi performansı sağlamaları ve kullanıcılar tarafından olus¸turulan isteklere en iyi bir biçimde hizmet sunmaları için onların yukarda belirlenen özelliklerini değiştirerek en  iyi  çalışacakları  duruma  gelmelerini    sağladık. Ancak  bazı  bu   özelliklerin değiştirildikleri zaman etkileri tepki süresi ve performans maliyeti üzerinde çok düşük bir seviyede olduklarından dolayı bu çalışmada bizim için bellek kapasitesi ve buna benzer olan ilginç ve etkili davranıs¸ları olan özellikler daha önemli olmaktadır. Bu sonuçlar çeşitli sistemlerdeki farklı yapılandırma ihtiyaçlarına göre farklı miktarlarda kullanılabilir olacak. Sonunda ise farklı özelliklerin sonuçlarını bir grafikte göstererek veri merkezlerinin hangilerinin kullanıcılara daha kaliteli servisler sunduğunu grafikteki noktaları kullanarak göstermeye çalışıyoruz. Bu grafikler bazı durumlarda, özellikle veri merkezlerinin kategorilerinin sınırlı bir biçimde değiştirilebilir oldukları zaman onların özelliklerinin daha hassas bir şekilde belirlenmesine yardımcı olurlar. Veri merkezlerinin kalitesi aslında oluşturucuların kalitesinde olması gerekmektedir. Veri merkezlerinin kullanıcı isteklerine istenen kalitede cevap vermeleri için özelliklerinin,   konumu   ve   algoritmasının   ayarlanması gerekmektedir. Kaliteli kablolar, güç dağıtım üniteleri soğutma sistemleri ve benzeri şeylerin sadece bir servis sunucusunun veri merkezi kurulumu konusunda sorunsuz olduğu zaman etkileyici olurlar. Örnek olarak NDCs’ın performansını gerçekten anlamamız için bu konuya herkesin bildiği ve kolayca anladığı bir biçimde yaklaşmamız gerekmektedir. ˙Içinde bulunduğumuz yüzyılda herkesin evinde, masasında ve hatta cebinde interneti bağlı olan cihazlar bulunmaktadır. Laptop, bilgisayar, TV ve tablet gibi cihazlar. Tüm bu cihazlar sürekli veri üretiyorlar ve CDC’lerdeki yönetim eksikliği  ve  aşırı derecede karmaşıklık performansın sorunlu olması ve garanti olmamasına  sebep olur. Günümüzdeki veri merkezleri sunucuları yönetmekte sıkıntı yas¸amaktalar. Bir kullanıcının isteklerine kaliteli bir servis sunulması için düzgün bir şekilde   planlama gerekmektedir. Sistemdeki  herkesin  ve  her  şeyin  birbiri  ile  uyumlu  bir biçimde çalışabilmesi gerekmektedir. Veri merkezlerinin ömrü boyunca sunuculardaki bazı bilinen sıkıntılar onların yapılmasında zorluklara neden olabilir. Mühendislik tasarımı ve yapılandırması, donanımların ömrünün bittiğindeki operasyonlar, donanımların tamiri ve güncellenmesi bu problemlerin bazısıdırlar. Dikkate  alınması  gereken başka sıkıntılar ise, bazı durumlarda kullanıcılar veri merkezleri alanında uzman olmayan bir firmayı tercih edebilirler veya kurucuların veri merkezi sistemlerini bilmiyor olabilirler. Bu bir sürekli olan kalite kontrolü meselesidir. Ayrıca buradaki söylenen problemler sıkça yaşanan problemlerdenler. Bunlarla karşılaşmak aslında her türlü kullanıcı ile çalıştığınız zaman mümkündür. Bazı büyük  firmalarda çalıs¸anlar arasındaki iletis¸im seviyesi çok düs¸ük olur veya küçük bir firmada sizin isteklerinizi kars¸ılayacak kaynaklar bulunmayabilir. Bu yetersizlikler çoğu zamanlarda kullanıcıların internet servisleri kalitesinden memnun kalmamalarına sebep olur ve internet servisi sunucuları servis kalitesinin garantilenmesi için hiçbir şey yapamazlar. Bunun  da  asıl  nedeni  ise  günümüzdeki  kullanılan  topoloji  ve  veri merkezlerinin modelidir. Internet tabanlı servislerin enerjiyi yetersiz kullanmaları ve kalite kontrolünün zorlaşması ve kişiselleştirmede sorun yaşamalarına da dikkat etmemiz lazım.We all know progress speed of technology is really fast and every day we encounter several new topics. Cloud computing is one of the recently emerging technologies in computer science. However cloud computing is almost new, There are lots of gaps that need attention. In our research we decide to consider data centers’ performance in cloud computing infrastructure. Huge amount of data is one of the serious problem in today’s world. This rising amount of data cause lack of management and current configuration of data centers could not satisfy consumer’s requests. We decide to investigate the performance of a specific kind of distributed approach instead of current centralized approach, to check if they could give better quality of services. For our experiment we use CloudAnalyst simulator which written in java and built on CloudSim (Buyya et al., 2009, p. 1265). By replacing a central data center with Nano data centers, we start to check their performance in comparison of central data center. Changing different properties of data center include: memory capacity, processor speed, bandwidth and number of user bases whom send requests to their local data center, we compare central and nano data center performance on different aspects like response time and performance cost, since these two factors are the most important factors we need them to be desirable. By interpreting our charts we show that our nano data centers works much better than central data centers. Finally we try to get some threshold point which our nano data center could give their best quality of services in. Actually we changed different properties of data center to find best point value that in which Nano data centers could reach their best performance and give better quality of services to their requests. However some properties has no impressive effect on response time or performance cost we try to do experiment more on those which act differently, like memory capacity. Also we conduct our experiments with some kind; of proportions between resources to obtain relativistic results. Finally we combine results of different properties two by two in one chart to show points which data centers give better quality of services with considering more than one properties. These kinds of analyses could be beneficial when for example we have a boundary for changing data centers’ categories and by referring to our charts could decide more precisely about constructing data center properties.Yüksek LisansM.Sc

Orchestrating datacenters and networks to facilitate the telecom cloud

In the Internet of services, information technology (IT) infrastructure providers play a critical role in making the services accessible to end-users. IT infrastructure providers host platforms and services in their datacenters (DCs). The cloud initiative has been accompanied by the introduction of new computing paradigms, such as Infrastructure as a Service (IaaS) and Software as a Service (SaaS), which have dramatically reduced the time and costs required to develop and deploy a service. However, transport networks become crucial to make services accessible to the user and to operate DCs. Transport networks are currently configured with big static fat pipes based on capacity over-provisioning aiming at guaranteeing traffic demand and other parameters committed in Service Level Agreement (SLA) contracts. Notwithstanding, such over-dimensioning adds high operational costs for DC operators and service providers. Therefore, new mechanisms to provide reconfiguration and adaptability of the transport network to reduce the amount of over-provisioned bandwidth are required. Although cloud-ready transport network architecture was introduced to handle the dynamic cloud and network interaction and Elastic Optical Networks (EONs) can facilitate elastic network operations, orchestration between the cloud and the interconnection network is eventually required to coordinate resources in both strata in a coherent manner. In addition, the explosion of Internet Protocol (IP)-based services requiring not only dynamic cloud and network interaction, but also additional service-specific SLA parameters and the expected benefits of Network Functions Virtualization (NFV), open the opportunity to telecom operators to exploit that cloud-ready transport network and their current infrastructure, to efficiently satisfy network requirements from the services. In the telecom cloud, a pay-per-use model can be offered to support services requiring resources from the transport network and its infrastructure. In this thesis, we study connectivity requirements from representative cloud-based services and explore connectivity models, architectures and orchestration schemes to satisfy them aiming at facilitating the telecom cloud. The main objective of this thesis is demonstrating, by means of analytical models and simulation, the viability of orchestrating DCs and networks to facilitate the telecom cloud. To achieve the main goal we first study the connectivity requirements for DC interconnection and services on a number of scenarios that require connectivity from the transport network. Specifically, we focus on studying DC federations, live-TV distribution, and 5G mobile networks. Next, we study different connectivity schemes, algorithms, and architectures aiming at satisfying those connectivity requirements. In particular, we study polling-based models for dynamic inter-DC connectivity and propose a novel notification-based connectivity scheme where inter-DC connectivity can be delegated to the network operator. Additionally, we explore virtual network topology provisioning models to support services that require service-specific SLA parameters on the telecom cloud. Finally, we focus on studying DC and network orchestration to fulfill simultaneously SLA contracts for a set of customers requiring connectivity from the transport network.En la Internet de los servicios, los proveedores de recursos relacionados con tecnologías de la información juegan un papel crítico haciéndolos accesibles a los usuarios como servicios. Dichos proveedores, hospedan plataformas y servicios en centros de datos. La oferta plataformas y servicios en la nube ha introducido nuevos paradigmas de computación tales como ofrecer la infraestructura como servicio, conocido como IaaS de sus siglas en inglés, y el software como servicio, SaaS. La disponibilidad de recursos en la nube, ha contribuido a la reducción de tiempos y costes para desarrollar y desplegar un servicio. Sin embargo, para permitir el acceso de los usuarios a los servicios así como para operar los centros de datos, las redes de transporte resultan imprescindibles. Actualmente, las redes de transporte están configuradas con conexiones estáticas y su capacidad sobredimensionada para garantizar la demanda de tráfico así como los distintos parámetros relacionados con el nivel de servicio acordado. No obstante, debido a que el exceso de capacidad en las conexiones se traduce en un elevado coste tanto para los operadores de los centros de datos como para los proveedores de servicios, son necesarios nuevos mecanismos que permitan adaptar y reconfigurar la red de forma eficiente de acuerdo a las nuevas necesidades de los servicios a los que dan soporte. A pesar de la introducción de arquitecturas que permiten la gestión de redes de transporte y su interacción con los servicios en la nube de forma dinámica, y de la irrupción de las redes ópticas elásticas, la orquestación entre la nube y la red es necesaria para coordinar de forma coherente los recursos en los distintos estratos. Además, la explosión de servicios basados el Protocolo de Internet, IP, que requieren tanto interacción dinámica con la red como parámetros particulares en los niveles de servicio además de los habituales, así como los beneficios que se esperan de la virtualización de funciones de red, representan una oportunidad para los operadores de red para explotar sus recursos y su infraestructura. La nube de operador permite ofrecer recursos del operador de red a los servicios, de forma similar a un sistema basado en pago por uso. En esta Tesis, se estudian requisitos de conectividad de servicios basados en la nube y se exploran modelos de conectividad, arquitecturas y modelos de orquestación que contribuyan a la realización de la nube de operador. El objetivo principal de esta Tesis es demostrar la viabilidad de la orquestación de centros de datos y redes para facilitar la nube de operador, mediante modelos analíticos y simulaciones. Con el fin de cumplir dicho objetivo, primero estudiamos los requisitos de conectividad para la interconexión de centros de datos y servicios en distintos escenarios que requieren conectividad en la red de transporte. En particular, nos centramos en el estudio de escenarios basados en federaciones de centros de datos, distribución de televisión en directo y la evolución de las redes móviles hacia 5G. A continuación, estudiamos distintos modelos de conectividad, algoritmos y arquitecturas para satisfacer los requisitos de conectividad. Estudiamos modelos de conectividad basados en sondeos para la interconexión de centros de datos y proponemos un modelo basado en notificaciones donde la gestión de la conectividad entre centros de datos se delega al operador de red. Estudiamos la provisión de redes virtuales para soportar en la nube de operador servicios que requieren parámetros específicos en los acuerdos de nivel de servicio además de los habituales. Finalmente, nos centramos en el estudio de la orquestación de centros de datos y redes con el objetivo de satisfacer de forma simultánea requisitos para distintos servicios.Postprint (published version

Contributions to the solution of the energy efficient file distribution problem

It has been realized that energy; one of the key requirements for modern human civilization, must be used efficiently for the civilization to be sustainable. The Information and Communications Technology (ICI) sector is no exception. It has been shown through research that ICT is consuming energy comparable to the aviation sector and is still increasing rapidly. In order to address this issue, many energy efficient approaches applicable to ICT sector have been proposed in the literature. In this Thesis, we pick one of the most ubiquitous task in ICT, file distribution and concentrate on finding ways of transferring a file from one server to many hosts in the most energy efficient manner. We study the problem for one server and many host problem but our algorithms can be applied to many general scenarios inducing P2P file distri­bution, replication of content in a doud, synchronization of caches in content distribution networks, downloading software updates to millions of PCs worldwide, and many more applications w here the data disseminated does not have to be consumed instantaneous y; for example, in video streaming. We study the problem for one server and many hosts but our algorithms can be applied to more general scenarios inducing P2P file distribution, replication of content in a doud, synchronization of caches in content distribution networks, downloading soft­ware updates to millions of PCs worldwide, We assume that the time is slotted and that the file is transferred in units of data called blocks. Each host can have arbitrary power consumption, upload and download capacities. To begin with, we prove that the prob­lem of energy efficient file distribution is NP-complete. In order to solve the problem optimally; we assume additional constraints and impose that all the hosts involved in the file transfer should have same upload and download capacity. Moreover; we also assume that the upload and download capacities are such that they are integral multi­ples of each other, which is typically the case. Under these conditions, we prove lower bounds on energy and design algorithms for file distribution that achieve the calculated lower bounds. Our algorithms minimize the amount of time a host has to be on to down­load and/ or upload in the distribution process. Apart from being theoretically sound, we also evaluate our model by extending our analysis through extensive numerical evaluation to compare the proposed algorithms with the already existing schemes of transfers. Our algorithms show promising improvement over not just the traditional energy agnostic approaches but also over the schemes designed for energy efficient file distribution. It has been shown that our algorithms are at least 50% more energy efficient than any of the proposals compared with. We advance our numerical analysis to relax the constraints in the theoretical analysis and conclude that our algorithms are also applicable in scenarios in which the comput­ing and networking hardware is energy efficient. Our algorithms can exploit the power proportionality of the devices. No efficiency comes without a cost. In this case, we pay the cost in terms of the tight synchronization that our algorithms require. However, we argue that such a tight syn­chronization at each slot level is possible in today's Internet particularly if the algorithms are applied to the hosts inside a corporation in which all the hosts and network are controlled by a central entity. For example, servers of a cloud, content distribution network, software updates inside a corporation, etc.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Fidel Cacheda Seijo.- Secretario: María Carmen Guerrero López.- Vocal: Guillermo Agustín Ibáñez Fernánde

Data-Driven Control, Modeling, and Forecasting for Residential Solar Power

Distributed solar generation is rising rapidly due to a continuing decline in the cost of solar modules. Most residential solar deployments today are grid-tied, enabling them to draw power from the grid when their local demand exceeds solar generation and feed power into the grid when their local solar generation exceeds demand. The electric grid was not designed to support such decentralized and intermittent energy generation by millions of individual users. This dramatic increase in solar power is placing increasing stress on the grid, which must continue to balance its supply and demand despite the potential for large solar fluctuations. To address the problem, this thesis proposes new data-driven techniques for better controlling, modeling, and forecasting residential solar power. The grid currently exercises no direct control over its connected solar capacity, but instead indirectly controls it by regulating new solar connections. This approach is highly inefficient and wastes much of the grid\u27s potential to transmit solar. Instead, we propose Software-defined Solar-powered (SDS) systems that dynamically regulate solar flow rates into the grid and design an SDS prototype, called SunShade. Specifically, we introduce a new class of Weighted Power Point Tracking (WPPT) algorithms, inspired by Maximum Power Point Tracking (MPPT), capable of dynamically enforcing both hard and relative caps on solar power, which enables the grid to decouple rate control from admission control. In contrast, to avoid grid regulations entirely, homes can also partially or entirely defect from the grid to fully utilize their solar power without restrictions. We present a switching architecture that enables homes to dynamically switch between a local generator, battery, and solar to co-optimize their cost, carbon footprint, switching frequency, and reliability. We introduce switching policies that reveal a tradeoff between solar utilization and reliability, such that higher solar utilization requires more switching, which can lead to lower reliability. Enabling better control of intermittent solar also requires improving solar performance models, which infer solar output based on current environmental conditions. Recent solar models primarily leverage data from ground-based weather stations, which may be far from solar sites and thus inaccurate. In addition, these weather stations report cloud cover---the most important metric for solar modeling---in coarse units of oktas. Instead, we propose developing solar models based on data from a new generation of Geostationary Operational Environmental Satellites (GOES-16 and GOES-17) that began launching in late 2017. We develop physical and machine learning (ML) models for solar performance modeling using both derived data products released by the National Oceanic and Atmospheric Administration (NOAA), as well as the satellites\u27 raw multispectral data. We find that ML-based models using the raw multispectral data are significantly more accurate than both physical models using derived data products, such as Downward Shortwave Radiation (DSR), and prior okta-based solar models. The raw multispectral data is also beneficial since it is available at much higher spatial and temporal resolutions---1km^2 and every 5 minutes---than oktas---25km^2 and every hour. The accuracy of our ML-based models on multispectral data is also better regardless of whether they are locally trained using data only from a particular solar site or globally trained using data from many solar sites. Since global models can be trained once but used anywhere, they can also enable accurate modeling for sites with limited data, e.g., newly installed solar sites. Solar forecasting models, which predict future solar output based on environmental conditions also help in better solar control. Accurate near-term solar forecasts on the order of minutes to an hour are particularly important because homes and the grid must be able to adapt to large sudden changes in solar output. Current solar forecasting techniques, which primarily use Numerical Weather Predictions (NWP) algorithms, mostly leverage physics-based modeling. These physics-based models are most appropriate for forecast horizons on the order of hours to days and not near-term forecasts on the order of minutes to an hour. While there is some recent work on analyzing images from ground-based sky cameras for accurate near-term solar forecasting, it requires installing additional infrastructure. We instead propose a general model for solar nowcasting from abundant and readily available multispectral satellite data using self-supervised learning. Specifically, we develop deep auto-regressive models using convolutional neural networks (CNN) and long short-term memory networks (LSTM) that are globally trained across multiple locations to predict raw future observations of the spatio-temporal data collected by the recently launched GOES-R series of satellites. Our model estimates a location\u27s future solar irradiance based on satellite observations, which we feed to a regression model trained on smaller site-specific solar data to provide near-term solar photovoltaic (PV) forecasts that account for site-specific characteristics