Data-Driven Modelling and Prediction of CoAP Throughput in a Grid Network Topology

Abstract

In this study, we propose new models for predicting the average throughput in a 4x4 grid Constrained Application Protocol (CoAP)-based IoT network using Support Vector Machine (SVM) and Multiple Linear Regression (MLR). Two different CoAP congestion control mechanisms have been considered: the default CoAP congestion control (CC) and the CoAP Simple Congestion Control/Advanced (CoCoA). On the client-side, we run 3, 6, 9, 12 or 15 CoAP clients requesting packets, sized with 12, 24, 36 or 48 bytes, from different CoAP servers over 4x4 grid IoT network configured with packet delivery ratios of 90, 95 or 100. In total, 60 different experimental scenarios, each of which was run 10 times to determine the average throughput of default CoAP CC and CoCoA clients, were created. Using 10-fold cross-validation, the performance of the prediction models has been evaluated using several performance metrics. The results show that combining packet delivery ratio and number of concurrently sending clients in a model leads to the highest correlation with the average CoAP throughput of the IoT network. Particularly, this model produces the lowest prediction error among all SVM-based and MLR-based models, regardless of whether the default CoAP CC or CoCoA is used as the congestion control mechanism. 

Keywords

• Internet of Things,Throughput Prediction

Bir Izgara Ağı Topolojisi Üzerinde CoAP’ın Veriye Dayalı Modellemesi ve Verimliliğinin Tahmini

Abstract

Bu çalışmada, Destek Vektör Makinesi (SVM) ve Çoklu Doğrusal Regresyon (MLR) kullanılarak 4x4’lük ızgara topolojisi üzerinde Kısıtlı Uygulama Protokolü (CoAP) tabanlı bir IoT ağındaki ortalama verimi tahmin etmek için yeni modeller önerilmektedir. İki farklı CoAP tıkanıklık kontrol mekanizması dikkate alınmıştır: mevcut CoAP tıkanıklık kontrolü (default CoAP CC) ve CoAP Simple Congestion Control/Advanced (CoCoA). İstemci tarafında, 90, 95 veya 100 paket teslimat oranları ile yapılandırılmış 4x4’lük ızgara IoT ağı üzerindeki farklı CoAP sunucularından, 12, 24, 36 veya 48 bayt boyutunda paket talep eden 3, 6, 9, 12 veya 15 CoAP istemcisi çalıştırılmıştır. Toplamda, mevcut CoAP CC ve CoCoA istemcilerinin ortalama verimini belirlemek için her biri 10 kez çalıştırılan 60 farklı deneysel senaryo oluşturulmuştur. 10 katlı çapraz doğrulama kullanılarak, tahmin modellerinin performansı çeşitli performans ölçümleri kullanılarak değerlendirilmiştir. Sonuçlar, paket teslim oranının ve aynı anda gönderen istemci sayısının aynı modelde birleştirilmesinin IoT ağının ortalama CoAP verimi ile en yüksek korelasyona sahip olduğunu göstermektedir. Özellikle, bu model varsayılan CoAP CC veya CoCoA'nın tıkanıklık kontrol mekanizmalarından bağımsız olarak, tüm SVM tabanlı ve MLR tabanlı modeller arasında en düşük tahmin hatasını üretmektedir.

Keywords

• Nesnelerin İnterneti

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